Given the inspiration of the looming Hubble Space Telescope deadline, I thought I would share some of my “big picture” views on crafting successful proposals, expanding significantly on the more succinct advice given in an earlier post. While I’ve developed these opinions based on my experience in astronomy, I suspect they’d apply to many other fields, both within and beyond science. So here goes…

A Proposal is a Highly Structured Rigorous Argument

In its most abstract form, a proposal is a piece of persuasive writing that lays out a convincing case that the proposed research is:

1. important
2. feasible
3. efficient

By “important”, I mean that the project must rise above the level of “good to do”, and instead be seen as “must be done”, even by people who don’t work in the field. By “feasible”, I mean that there must be a clear path to a definitive scientific result. By “efficient”, I mean that the particular approach you’ve taken is the optimal one for reaching the important goals you’re targeting (i.e. aim for “Studying X provides the cleanest test of Important Science Y” and avoid building a proposal to study X when studying Z is clearly a more direct approach to Important Science Y — even if you worked on X for your thesis.)

You should lay out your arguments for Every. Single. One. of these cases before you write a single word of latex. Why? Because proposals live or die not on the beauty of your prose, but on the structure of your argument. If the reviewer does not believe that you’ve made the case for importance, feasibility, and efficiency, you’re done.

Here’s how I do this. Although I’m sure it will seem remedial to many of you, and reveal me as the anal geek that I am, I start a stupid ASCII file with two sections:

1. Selling Points
2. Potential Weaknesses to Shore Up

I then start filling out each with short bullet points listing every possible argument for or against what I’m proposing.

The selling points should be fairly easy, since you’re likely to write proposals for things you are inclined to think are awesome. Do, however, avoid the pitfall of conflating “important to me” with “important to Science”. Just because you would really like to know more about some property of something you’re interested in, doesn’t mean that other people will naturally share your enthusiasm. Keep your eye on the big picture.

The “Potential Weaknesses” section can be a bit trickier, since you need to channel your inner crabby reviewer. Think of every nit-picky, outside the box criticism one could throw at your idea, and every area where a reviewer could get confused. (As an example, here’s a list of some of the self-criticisms I came up with for an HST proposal for NIR observations of nearby galaxies a few years back: “What about AO from the ground?” “Why this many targets — how many do you actually need?” “What about dust (i.e. is 1 NIR filter OK)?” “Are the models really in need of improvement?” “How can we claim to do galaxy science while simultaneously arguing that the models aren’t yet up to it?” “Are the results confused depending on fraction of O-rich vs C-rich AGB?” etc).

In short, the “Selling Points” section is about demonstrating “importance”, and the “Potential Weaknesses” section is about assessing “feasibility” and “efficiency”.

After you’ve got an initial list, you have to step back, evaluate, and edit.

• Go through the selling points and prioritize. Decide what the “main message” of your proposal is, based on which bullet points speak most effectively to the larger importance of what you’re proposing. If your ideas are strong, you’ll usually find that several of the most compelling bullet points will group together and can be ordered to tell a single story. You’ll also find that some of the bullet points will not naturally fit within that narrative. Identify this subset of arguments that are “nice, but not compelling”. You’ll want to be sure to minimize these in the proposal, to avoid their distracting from a more central idea. I speak from experience when I say that you really do not want to confuse the reviewers about what your proposal is about (i.e. It’s better to have something like “Dark Matter! Dark Matter! Dark Matter! and by the way it also tells you something about planets, frogs, and quark stars” rather than “Dark Matter! Planets! Frogs! Quark Stars!”, since the latter leads to complaints from the reviewers that while they believed your dark matter ideas, you had not fully fleshed out a compelling case for the frog science.)
• For each entry in the “Potential Weakness” section, write down any brief ideas about addressing those concerns (something like “Make figure showing evolution of models with time” “Check number of stars expected and compare to sizes of Galactic samples”, etc). You don’t have to come up with definitive answers, but you should lay out a road map for what you need to do to make your experiment look feasible and efficient.

At this point, I sometimes make a third section and list a few figures that seem like they support the key scientific ideas, or that shore up some of the obvious weaknesses.

Now that you have this silly little ASCII file (which you shouldn’t spend more than a day on, if that), send it to your collaborators. Get their feedback about what they think the strongest selling points are, what their additional concerns are, and what arguments they would use to shore up weaknesses. Expand the file accordingly, so you have a record of everything that you think needs to go into the proposal. You’ll probably find that it’s a huge time savings to get this to your collaborators in this form, before you have a 10 page latex file with embedded figures. If you do the latter, your collaborator will likely come back and say “You know, I think the reviewers are going to be way more interested in frogs”, at which point you have to chuck out weeks of work. With this method, you get feedback quickly (since they have to skim a very short list of bullet points), and you don’t have a lot of sunk costs if you decide to overhaul the arguement.

At this point you’ll have a document that summarizes your rhetorical argument. Your case will be laid out so that you can easily evaluate it on its scientific merits. So, before you dive into writing, you need to step back and decide if you’ve actually constructed a strong case. Sometimes, it will become obvious that there are too many weaknesses to address, and that it’s going to be an uphill battle to convince anyone that this needs to be done. If that’s the case DON’T WRITE THE PROPOSAL! I have probably a half dozen of these ASCII files where I spent half a day deciding that I didn’t, in fact, have a compelling project, and I’d be better off investing my time elsewhere. That’s OK! The exercise of structuring your argument first is designed to be fast, so you don’t sink much time in before you decide whether to continue or not.

Once you (and your collaborators) are convinced that you do in fact have a strong case, you need to start building the actual text. I frequently will estimate the number of paragraphs I expect to have for my scientific justification (usually 2.5-3 per page), and then make an enumerated list showing how the argument will flow through the paragraphs. This exercise helps to keep the text following the structure of the argument, so that it builds to make the main points. It also helps me to figure out when I’m trying to cram too much information in.

If you’ve gone through all of the above, you’ll find that the proposal will almost write itself. You will have cleanly separated “generating text” from “generating a compelling project”, such that you know exactly what you want to convey, and what the text needs to accomplish. Generating lovely English sentences at this point is much easier.

My original idea was to summarize what I thought was the best advice, and turn it into a single post. This idea has been undermined by (1) me not knowing which advice is best, and (2) a wide variety of occasionally-contradictory advice, presumably all applicable in different circumstances.

So instead here I’m just going to link to some of the most promising-looking resources that were mentioned. I encourage you to read the comments on the original post to get more ideas, and chime in here to keep the conversation going.

Collections of Online Resources

• The Alternative Scientist (blog)
• Non-Academic Career Information — a fantastic compendium from Prodigal Academic
• PhDs.org: Career Resources
• Beyond Physics: From the University to the Work Market (Facebook group)

Discussion Forums

• APS Forum on Graduate Student Affairs — Non-Traditional Careers
• Leaving Academe Forum — Chronicle of Higher Education
• Science Careers Forum — AAAS
• Versatile Ph.D.

Specific Kinds of Jobs

• Mathematics in Industry — SIAM
• Non-Academic Astronomers Network — AAS
• Policy Fellowships for Scientists and Engineers — a comprehensive list from Sheril Kirshenbaum
• What Is Data Science? — Mike Loukides
• How to Get a Job in Physics — Graduate course at LSU by Jorge Pullin
• Alternative Careers for Scientists — Bitesize Bio
• Careers in Science Policy — Heather Rieff

Personal Stories/Advice

• Project for Non-Academic Science — Guest-blog accounts collected by Chad Orzel
• Academia vs. Industry (Math) — Mark Chu-Carroll

Books

• Alternative Careers in Science — Cynthia Robbins-Roth
• Put Your Science to Work — Peter Fiske
• So What Are You Going to Do With That? — Susan Basalla and Maggie Debelius

Job Ads/Finders

• Government Jobs Finder
• Science JobSeeker — AAAS
• Nature Jobs
• New Scientist Jobs
• The Scientist Careers

I always try to be honest with my own students about the prospects for ultimately landing a faculty job. But like most faculty members, I’m not that much help when it comes to outside opportunities, having spent practically all my life within academia. I’m happy to give advice, but you’d be crazy to take it, since I have no idea what I am talking about.

But that’s a correctable state of affairs. So: I’m hereby soliciting good, specific career advice and/or resources for students who are on the track to get a Ph.D. (or already have one) and are interested in pursuing non-academic jobs. This might be particular jobs that are Ph.D.-friendly, or websites with good information, or relevant fellowships or employment agencies, or just pointers to other resources. (For example: do you know the difference between a CV and a resume?) The more specific the better, and including useful links is best of all. General griping and expressions of bitterness should be kept in the previous thread; let’s try to be productive. And there’s no reason to limit it to physics, all fields are welcome. Advice that is useful for only a tiny number of people, but extremely useful for them, is certainly sought. We’re looking for things that have a nontrivial chance of actually helping some specific person at a future date.

Most of all it would be great to have input from people who actually got a Ph.D. and then went on to do something else. But it’s the internet, everyone can chime in.

I will take what look like the most helpful suggestions and collate them into a separate post. Spread the word, let’s get as much input from different sectors as we can.

However.

I have to point out that the advice is very heavily weighted not towards “tenure at a major research university” but instead towards “tenure at one of the top 10 schools in the US”.  As evidence, here is a plot of the latest NRC rankings (red) and US News rankings (blue) of physics departments (shamelessly lifted from here — thanks HappyQuark!).  I have helpfully circled in green the departments where Sean has been on the faculty:

Now, this is not saying that much of Sean’s advice isn’t generally applicable, but one should recognize that the vast majority of people who may be seeking tenure advice are not going to be at institutions with tenure criteria as strict as the ones Sean is considering.  There are scads of fantastic scientists doing interesting work at places that aren’t in the top 5 of the NRC rankings, and probabilistically speaking, you’re more likely to be working towards tenure at one of those.  While MIT may have a <50% tenure rate, the odds are far better at many institutions.

Personally, I found Sean’s advice really really dispiriting, and it probably would have freaked me out to read it as a postdoc. And yet, I find myself with “tenure at a major research university” without ever having lost sleep to fears about achieving seemingly impossible standards.  I worked steadily, but not insanely.  I had a couple of kids.   I “dabbled” in other research areas, some of which turned into major research areas down the road.  And it worked out (although, it likely wouldn’t have “worked out” if I was at Chicago or Caltech).

I think if one wants to make a more general statement about “how to achieve tenure”, I think the key is to show that you’ve got “traction”.  Look at recently tenured (<10 years) people in your particular department at your particular university, and evaluate what they tend to do well (say, undergraduate teaching if you’re at Swarthmore, or running giant experiments if you’re at Harvard). Then, demonstrate that you’ve got traction that is pulling you in that direction.

For example, if all the tenured faculty have research grants and students, and you don’t, then you’ll appear to be spinning your wheels.   Instead, if you have a grant or two, and are showing increasing success with your proposals, the tenure committee can believe that you’re evolving into what the department expects of its tenured faculty.  For most universities, you don’t always need to be completely at your destination, but you need to show that you’re actually traveling down the proper path at a decent clip.  The closer you are to the destination, the better your chances, and the more competitive the tenure process, the closer you’d better be.  (Sean’s point about “firing on fear” is basically saying that a tenure denial is based on their fears that you will not wind up getting to where they need/want you to be.)

The final point I’d like to make is my concern that Sean’s fairly conservative prescription eliminates the real “upside potential” of taking risks.  A colleague and I have had many discussions about the fact that, because we were more than willing to leave academia, we were more willing to take risks.  These risks paid off in more interesting research than the path we were headed down as young postdocs.  (The one caveat is paying attention to timescale though — trying to establish a new field of research won’t be a good bet if it takes 10 years to pull off.)

In summary, while Sean’s suggestions are excellent rules for guaranteeing tenure in a physics department at any university in the US (especially that one about being a productive genius!), you can still likely achieve tenure with a less terrifying set of recommendations.

This is the time of year when prospective graduate students are visiting different universities, deciding where they will spend the most formative years of their scientific lives. Amidst the enthusiastic sales pitches, I try to make sure to remind everyone that the odds of success are long — there is a bottleneck that shrinks as you go from grad school to postdoc to junior faculty to tenure. Probably the biggest hurdle is the leap from postdoc to junior faculty; it’s easier to get tenure once you’re a professor (statistically speaking) than to become a professor in the first place.

But it’s not guaranteed! As many of you know, I was denied tenure myself. This actually puts me in a pretty strong position to talk about the ins and outs of what it takes to succeed, having seen lack-of-success (is there a word for that?) up close and personal. I’ve avoided talking too much about this topic, partly because armchair psychologists have trouble resisting the temptation to take anything general I would say and attempting to match it to specific people and aspects in my own case, despite a pretty thorough lack of familiarity with the facts. On the other hand, maybe I can offer some actually useful guidance to people who are trying to do something difficult and important for their future lives.

So here goes: how to get tenure. But first, caveats. My own experience from grad school on has been at top research places, so those are the only ones I can speak usefully about; the situation will generally be very different at places that put more of an emphasis on teaching, for example. So really I’m talking about places that think of themselves as being in the top 10 or so in their research fields. And of course, to every set of rules there are exceptions; it’s not hard to find people who violated one or more of these guidelines, so don’t take them as written in stone. Every case, and every department, is different. Finally, don’t think of these as too bitter or cynical; I’m simply trying to be honest, with perhaps a small slant to counteract some of the misinformation that is out there. (This misinformation doesn’t usually arise from willful lying, but from the slightly schizophrenic nature of the mission of research universities; see The Purpose of Harvard is Not to Educate People.) I’m generally in favor of the tenure system; like democracy, it’s the worst system out there, except for all the other ones that have ever been invented.

With all that throat-clearing out of the way, let’s get down to brass tacks. Here is the Overriding Principle: what major research universities care about is research. That’s all. Nothing else. But even once you recognize that, there is still some craft involved in shaping your research career in the right way. This isn’t the place for me to pass judgment on this principle; I’m just elucidating its consequences. This is a how-to manual for the real world, not a roadmap for Utopia.

You’ll be pleased to learn that there are actually two different routes to getting tenure, so you can choose which one works better for you. The first one is simple to describe, and comes down to a single suggestion:

• Be a productive genius. This deserves to be classified as a separate technique because, for the small number of easily-recognized true geniuses out there, the rest of the suggestions below are beside the point. Do whatever else you like, as long as you are revolutionizing the field on a regular basis. It’s worth stressing the word “productive,” though. The trash heap of history is littered with geniuses who thought it was beneath their dignity to actually produce anything; that won’t fly, generally speaking, in this game. So if the genius thing is working out for you, great; just be sure to put it to productive use, and you’ll be fine.

The rest of us schlubs, on the other hand, need a more explicit checklist. So here’s what ordinary people should try to do if they have a junior faculty job at a major research university, and would like to get tenure.

• Do good research. This is obvious, right? So I’m not going to belabor it.
• Be prolific and reliable. No, tenure is not given or denied simply on the basis of how many papers you write. But… it doesn’t hurt. More importantly, if there is some standard of productivity in your field, try to maintain it all the time. Don’t have “a bad year.” Because if you have one bad year, who knows how many bad years you’ll have in the future?
• Be technically sound. Quality is sometimes hard to judge. But among different types of quality, it’s a bit easier to recognize “technical” ability — whether it’s doing fearsomely complicated calculations, or huge computer simulations, or what have you — than more “creative” or “imaginative” contributions. (To be clear: creativity is good, not bad. It’s just hard to quantify.) George Gamow, a very creative guy, had trouble getting a job at a top place because there were worries about his technical ability. And he practically invented the early universe as we know it.
• Make an impact in the field. It’s not enough to do good work; your work has to be recognized as good. The single most important part of your tenure file is the letters from experts at other universities, comparing you to the best young people in your area. If any of them come back saying “I’ve never heard of this person,” it’s the kiss of death.
• Get your name on something. A slight exaggeration, but if you have something named after you — a theorem, an experiment, a model — it’s a big help. The larger principle is that your contributions should be specific, not vague. Good: “she invented model A.” Bad: “she did major work in B, and was one of the first to think about C.” In Hollywood terms, have an elevator pitch. It’s easier for people to think about what you’ve done if it can be summed up in a sentence. When people ask “what was your major contribution?” have an answer ready.
• Don’t be too well known outside the field. I hate to say this, but the evidence is there: if you have too high of a public profile, people look at you suspiciously. Actual quote: “I’m glad we didn’t hire Dr. X; he spends too much time in the New York Times and not enough time in the lab.” And that’s the point — it’s not that people are jealous that you are popular, it’s that they are suspicious you care about publicity more than you do about research. Remember the Overriding Principle.
• Don’t write a book. This follows partly from the above; if you’re contemplating writing a popular book, and aren’t sure whether it will negatively impact your chance of getting tenure, you’re probably too far gone for this list to even help you. But it’s worth a separate bullet point because even textbooks are beyond the pale. (Probably the worst thing I personally did was to write Spacetime and Geometry.) You might think that a long volume filled with equations that provides a real service to the community would help your case. It won’t; it will hurt it. Why? Because while you were writing that book, you weren’t doing research. Catching on? (Obviously I’m writing from a field where research is conveyed solely through papers, not books; if you’re in a field where the serious research is contained within scholarly books, then by all means write all the scholarly books you can.)
• Bring in grant money. Thanks to Steinn in comments for mentioning this one. Getting grants is a big help, because (1) money is good, and (2) it’s extremely quantifiable.
• Take outside offers seriously. If another top place is interested in you, don’t just jump on it, but don’t blow them off, either; pursue the possibility, and let it be known that you are pursuing it. If you would really like to stay where you are and worry that they will let you go without a fight, squelch that worry. Maybe they will let you go, but if so, there is a strong possibility that they weren’t that interested in keeping you. (Duh.) Also, it always helps to be popular; professors are people too, and can be influenced by the opinions of others.
• Don’t worry about teaching, leadership, organizing, etc. I don’t think being good at these things actively hurts you, although I did once hear a senior faculty member say that he was negatively predisposed to candidates who had good teaching evaluations. (He was joking, I think.) Why? Because you’re spending time on something that isn’t research. But generally it won’t hurt, it just won’t help. You will typically be told (as I was) something like “teaching isn’t really important, but if your case is very close, it can help put you over the top.” Everyone agreed my case was very close, and my teaching was among the best in the department; it didn’t help. The point is simple: this stuff is not research.
• Choose your hobbies wisely. This is a bit more subjective, but I think there is some truth here. Even the highest-pressure departments in the world don’t think that faculty members can’t have any hobbies outside their work. But here is the paradox: you are better off if your hobbies are nothing like your work. Permissible hobbies include skydiving, playing guitar, or cooking. Suspicious hobbies include writing of any sort (novels, magazine articles, blogs), programming or web stuff, starting a business, etc. Why? Because there’s a feeling that this kind of activity represents time that could be spent on research. I don’t think blogging has quite the stigma it once did, although I have heard senior faculty members say they would never hire someone with a blog. But it’s a symptom of a willingness to spend your intellectual energies on something other than doing research.
• Friends are good; enemies are bad; indifference is fine. There can be an element of personal politics involved in tenure decisions, although this is usually exaggerated by outsiders who don’t know much about the substantive issues. It is important to have people within the department who are respected and will make a strong affirmative case for you. It is also bad to have people within the department, especially respected ones, who are against you. (Tenure usually doesn’t just require a majority vote, it requires a strong consensus within your department.) But interestingly, it doesn’t matter that much if many people in the department don’t care one way or the other. They are usually happy to go along with the respected people closest to you academically, especially if they indicate strong support. You don’t need to be friends with everyone, just the right people.
• Don’t dabble. Another slightly counter-intuitive one. You might think that, while most of your research work is in area A, the fact that you wrote a couple of papers in area B will be taken as positive evidence of your breadth and intellectual strength. Very wrong. What will actually happen is that your work in area B will be compared to the best people in the world who spend all their time thinking about area B, and you will probably come up wanting. Even worse, it will be taken as evidence that your interests may wander over time — so that, whereas you were hired to be an expert in area A, maybe in a few years you won’t be doing that at all. Kiss of death. Deep down, there is a strongly anti-intellectual strain within academia; you were hired to work in a specialty and that’s what they expect you to do. Once you get tenure, of course, you can do whatever you want; so it’s important that the department be reassured that you don’t want to do anything else.

Again, some of this may seem a bit cynical, but I’m trying to put things as strongly as possible so the message isn’t garbled by well-intentioned pieties. It’s certainly possible to get tenure while violating some of the above rules, but the trend should be clear. Let’s put it this way:

Places hire on hope, and fire on fear.

When you get hired, the facts that you are interdisciplinary and a good teacher and a strong leader all work to your advantage, because these really are good things. The people who hire you are sincere when they give you compliments for these qualities. What you don’t know is that, at the faculty meeting where they voted to hire you, inevitably someone said “Why are we thinking so hard about this? It’s a junior faculty job. Let’s just take the risk, and if they don’t work out they won’t get tenure.”

The tenure decision is very different than the hiring decision. When you get hired, everyone can afford to be optimistic; you are an experiment and you might just hit paydirt. When you come up for tenure, the prevailing emotion is one of worry. Even the biggest departments don’t get to hire that many people; tenured slots are extremely valuable and rare commodities. They are committing to you for the next three decades. And what scares them to death is that you will stop being a productive researcher. And any evidence that you enjoy doing things other than research within the field in which you were originally hired is, like it or not, possible evidence that you will drift away from your core mission once you achieve tenure. We all know senior people in good departments who are no longer productive; don’t give your department any reason to suspect that you will become one of those people.

Of course, there are things in life that you might judge to be more important. These aren’t guidelines about how to live your life, only about how to get tenure. It’s up to you to decide whether following them represents a sacrifice you are not willing to make. Nobody gets into this job for the money or the glory; career considerations aside, you have to make sure you’re having fun and chasing your passions. Good luck!

Unfortunately, AAS presentations are almost entirely 5 minute talks, in contrast to the more typical 50 minute colloquia on which we’ve all cut our teeth.  This short format presents a real challenge, and requires a very different approach.  So, in CV’s long running Unsolicited Advice series, I now give my basic guidelines for writing a short talk.

1. In a 5 minute talk, you can usually only teach people about one new thing.  The key to framing the talk is to figure out that One New Thing, and then build the rest of the talk around it.

2. So, the very first step is to pick the absolute best single visual to show the One New Thing.  This is usually an awesome plot.

3. Make this plot the first slide you prepare.  Don’t start with history and motivation and data acquisition and analysis techniques — if you do, you’ll prepare way too much material, and find yourself at 4 minutes and 59 seconds without having actually gotten to your results.  Instead, generate the one or two slides that show the One New Thing, and explain its meaning.   (If it helps, think of this as “How would I explain my results, if someone walked into my office and asked what I was working on?”  In all likelihood, you’d pull out the coolest plot, and start explaining it.)  If there are multiple features to explain about the awesome plot, consider repeating the plot on multiple slides, and explaining one feature of the plot on each slide.

4. Now, work backwards.  What are the essential facts needed to understand the plot and appreciate its awesomeness?   Operationally, this usually means one or two slides of motivation (covering why this is an interesting topic, and why there are questions that still need to be answered) and one or two slides describing the data and/or analysis (covering just enough that people understand the outline of what you’ve done, and accept the validity of your approach).

5. When presenting these essential facts, you have to return to the point in Step 1.  Since you can’t teach people more than one new thing in a 5 minute talk, your motivation/data/analysis slides should function more as “reminders” of what people already know.   Your audience has read a lot of papers, have done lots of observations, have written many analysis codes, and have seen tons of colloquia — since most will have this background, all you really need to do is trigger the right memories.  Note that this is different than assuming your audience are experts on your particular project — you still want to walk them through the essential facts from Step 4.  However, you don’t need to explain what the VLA is, nor do you need to explain anything that would be routinely covered in beginning graduate coursework.  Reminding people?  Yes.  Explaining details of routine astronomical tools?  No.

6. Add a conclusion slide to the end of your talk, ideally with two or fewer take home messages. Do not recap what you did.  If you can, reproduce the plot for your One New Thing.

7. Now, go back through your whole talk, and eliminate every single word you possibly can.  Turn sentences into phrases (i.e. “We took 2000 DEIMOS spectra with 8 hour exposure times in Spring 2008″ becomes “2000 DEIMOS spectra”).  Eliminate any details that aren’t essential facts. You simply don’t have time to effectively convey nuance and complexity, so you need to strip such frippery.   You are trying to keep your audience on track, and do not want them distracted by unnecessary detail.  Rule of thumb: If you have to use smaller than 48 pt font, you’ve got too many words.

8. Take yet another pass through your talk, working on making the visuals as clear as possible.   Use Powerpoint/Keynote to generate new >48 pt axis labels for all plots.  Add arrows and text boxes to point out key features in plots.  Make sure all point symbols are clearly explained, and can be easily distinguished from 50 feet away (i.e. open and closed symbols of contrasting colors are better than X’s and crosses).   Eliminate all yellow or orange symbols from white backgrounds, since no one can ever see them when projected.  If there are additional lines on your plot that you will not have time to talk about (i.e. from fits, or models), remake the plot without the lines, or hide them behind white lines.  Adjust the image contrast and/or line thickness to make all lines and symbols beefier, and easier to see from far away.

9.  Finally, practice your talk, ideally with a helpful non-expert colleague roped into watching.   Find out what parts they didn’t understand, and fix them.

So, best wishes, and see you in Seattle!

This morning the New York Times has an article on “study habits”. It argues against the conventional wisdom (find a clean, neutral space, and bear down on a single topic), and in favor of what might be called intellectual cross-training: “alternating study environments, mixing content, spacing study sessions, self-testing”. The basic philosophy seems to be encapsulated:

“The idea is that forgetting is the friend of learning,” said Dr. Kornell. “When you forget something, it allows you to relearn, and do so effectively, the next time you see it.”…The harder it is to remember something, the harder it is to later forget.

You want to revisit the relevant material multiple times, in different contexts. And, in case you were wondering, all-nighters do not qualify:

Cognitive scientists do not deny that honest-to-goodness cramming can lead to a better grade on a given exam. But hurriedly jam-packing a brain is akin to speed-packing a cheap suitcase, as most students quickly learn — it holds its new load for a while, then most everything falls out. “With many students, it’s not like they can’t remember the material” when they move to a more advanced class, said Henry L. Roediger III, a psychologist at Washington University in St. Louis. “It’s like they’ve never seen it before.”

Intermittent study sessions, coupled with testing, helps ensure comprehension and retention. And why not throw in some quantum mechanics?:

Dr. Roediger uses the analogy of the Heisenberg uncertainty principle in physics, which holds that the act of measuring a property of a particle alters that property: “Testing not only measures knowledge but changes it,” he says — and, happily, in the direction of more certainty, not less.

I certainly wouldn’t take any of this as gospel. The article is full of anecdotal statements of this sort: “The children who had studied mixed sets did twice as well as the others, outscoring them 77 percent to 38 percent. The researchers have found the same in experiments involving adults and younger children.” We are not told how many children were involved in the studies, nor what the “error bars” might be. On the other hand, many of the suggestions are consistent with my personal experience. I often seek out new and different places to work, finding that changing the venue paradoxically helps me focus and facilitates progress. In addition, at any given time I’m often working on a number of different topics, and alternating between them seems to increase my clarity and productivity. I think the real message is that everyone is different, and there’s no “magic desk” to ensure that you become organized and brilliant. One thing that does seem apparent: hiding away in the corner for days at a time struggling with a single topic is not necessarily the road to enlightenment.

So, good luck with all that decision-making! Here are links to our previous posts about the topic.

• Unsolicited Advice: Choosing a Grad School
• On Choosing a Grad School: A Dialogue
• Unsolicited Advice: Choosing an Undergraduate School

Not too much to add to the discussion there, but here’s an opportunity to chat about the process. My own strong feeling is that how successful you are in school (grad or undergrad) is much more up to you than up to the institution. Most places have more good opportunities than anyone can hope to take advantage of in a limited period of time. Take the initiative, don’t wait for good things to come to you, and have fun!

Unfortunately the video doesn’t seem to be embeddable, but you can go to the video page and click on the “David Gross” entry. (The others are good, too!)

You all know my perspective here — time probably exists, and we should try to understand it rather than replace it. But I’ll agree with David — let’s not ignore more “practical” problems, but not be afraid to tackle the big ideas!

On the one hand, nobody likes a cluttered slide. In science lectures it’s much better to show a single plot augmented with a verrrry limited amount of text. The clarity focuses the student on the most important point, and frees them to actually listen to what you’re saying.

On the other hand, it’s useful for the students to have a more detailed record of what you discussed while explaining the plot. Yes, they can and should take notes, but there is a natural tendency for students to write down Every. Word. You. Say., since they have no context for prioritizing the importance of the information spewing forth. I prefer to be explicit about what the key points are.

My trick for balancing this is using black text on a black background. The text doesn’t show on the screen, but it does show up when printed as a handout, since the black background defaults back to white. Thus, you get the following:

1. Topic X is important and interesting.

2. But.

3. This is how we will address “But.”

The rest of the proposal reiterates those three points with enough detail to make it believable.

In a short proposal, the structure fills a paragraph. In a long proposal, it’s three paragraphs, and shouldn’t go past the first page.

The abstract is a 1 paragraph version of the same structure, with the addition of a closing rah rah rah sentence.

If you can’t bludgeon your introduction into this form, you might want to step back and regroup.

This was my last meeting – I have served on the committee for six years. The membership rotates roughly every two years. I had been an external reviewer and problem writer for a couple years, and was then asked to serve on the committee. I am sworn to secrecy about a lot of the details, for good reason, but let me try to tell you from my perspective as an exam writer how to study for this dreaded event in your physics education.

Firstly, there’s the format. The exam is 100 questions long, and you have 170 minutes to do it. This is, therefore, different from just about every other physics exam you have had in college, where you have, say, four to six problems in an hour-long exam. The GRE Physics problems (or “items” in assessment world jargon) are short, to-the-point questions, and just about all of them are short calculations, if any, and take little time once you see what to do. Writing such questions is a difficult thing to do, let me tell you. We are continually amazed how, after about six levels of review, we can find issues of clarity, reasoning, and even sometimes basic physics correctness in the items submitted to the pool. All the committee members spend a lot of time each year reviewing hundreds of problems, looking for flaws, but more often than you would think the face-to-face meeting in Princeton with the ETS folks reveals something previously overlooked. It’s a really interesting process.

For each new exam form we eventually arrive at 100 items that test mastery of a clear physics concept or idea, and there is, yes, a certain amount of memorization required in terms of the basic equations learned in undergraduate physics. But there are many problems that can be done using just concepts, and many that can be done with simple dimensional analysis. When there are numerical solutions (and many if not most are in that category) the numbers are chosen so as to allow easy arithmetic – no calculators are allowed.

My first piece of advice to students studying for this exam is to focus on reviewing the textbook from your freshman introductory physics course. In my years on the GRE committee, when I have needed to consult a text, it is that text at least 80% of the time. If you master every example in there and review the basic equations, you will do really well on the GRE. I have found that only a small fraction of the items on the GRE are actually from upper-level topics like stat mech, quantum, and special topics (solid state, nuclear, particle, cosmology, etc.) And presumably you have been studying the advanced topics more recently anyway. I think the single biggest mistake students make in studying for the GRE is to focus on too-advanced subjects.

The other piece of advice I give students is to be disciplined in your approach to actually taking the exam. You only have an average of 1.7 minutes per problem! If you get bogged down on a long algebraic calculation, you risk not being able to complete the exam, including items that you would correctly answer in a few seconds. So when you take the exam, read each problem, answer it if you can do so reasonably quickly and then put an X on the problem number. If you think the problem will take some time or a long calculation, put a circle around the number and come back to it in a second pass through the whole thing. But pIck off the easy ones first! It also helps build confidence as you go through.

Also realize that the GRE penalizes random guessing: your raw score is the number correct minus the 1/4 times the number incorrect. As a result it’s no better to guess than to leave an answer blank if you cannot eliminate some of the five choices. But if you can eliminate some, then by all means guess! Look carefully at the possible answers – sometimes just the units, or magnitude, or mathematical form can give you a way to guess more astutely.

So just what is the GRE measuring? A critic might point out that it measures the ability to work under pressure, memorization, and quick mathematical reasoning and calculation. Though these are good qualities for a physicist to have, they are by no means the only qualities required for a successful career. I would argue further, though, that the Physics GRE really does test knowledge about basic physics and the ability to analyze physical situations accurately.

So then how important is the Physics GRE for your career? It turns out that it is in fact quite important. Some of the top programs in the US even go to the extent of requiring a GRE score above some threshold for considering the applicant. I have served on our graduate admissions committee for five years now, and I can tell you that we regard the GRE as just one piece of information telling us how likely a student is to thrive in our program. We do see a clear correlation between an incoming graduate student’s Physics GRE score and their score on the other dreaded exam in a physics student’s career, the Ph.D. written preliminary exam, which is a very different beast. (There was, a few years back, some lore that the GRE Verbal score was a better predictor than the GRE Physics score, and there is a correlation, but not as strong as with the GRE Physics score.)

In considering an applicant we look at a number of things, including the applicant’s own statement, experience, letters of recommendation, and their undergraduate transcript, in addition to the GRE general and subject scores, to get an idea of the whole student. My own observation is that students below about the 30% level have a very hard time attaining a Ph.D., though this is by no means absolute. I am sure there are tons of very successful physicists out there who, for whatever reason, scored poorly on this peculiar exam and went on to great careers.

So, to of those of you facing this exam in a few weeks, I wish you good luck! Review your intro course, get a good night’s sleep before the exam, and make sure you pick off all the easy problems that you can!

After you read enough letters, they can start blend together. But, in a big stack of applications, there are usually a few letters that stand out as risible, causing a good chuckle and round of comment from the committee.

And they are almost always letters written on behalf of women.

In a standard letter of recommendation at the postdoc/faculty level, there is frequently a comparison to other successful scientists. The letter usually reads something like “reminds me of person X, Y, or Z at a similar level of their career” or “shows the same persistence and insight as person Q, and stronger big picture thinking than person P”. These comparisons are almost always favorable, saying that the applicant is in the same league as other people who are recognized as having had a significant scientific impact.

But, for some reason, some fraction of letter writers insist upon doing these comparisons only within a single gender, when the applicant is a woman. In other words, “(woman) X shows a similar level of insight as (woman) Y and (woman) Z”. I’m not saying that these comparisons are not favorable — they’re usually comparing a strong female applicant favorably with other successful female scientists. Their praise is genuine and well meant. However, one can’t but help perceive that they see women as somehow swimming in a different pool than the rest of the guys.

Now the good news is that most committees that I’ve been on have seen right through this. We note it, and have a small laugh at the letter writer’s expense. In addition, it’s not common — usually only affecting a couple of letters in an applicant pool.

So, if you’re writing a letter for someone in an underrepresented group, please save yourself from mockery by examining exactly how you perceive the applicant’s comparison sample.

For the many international CV readers, today is the US’s Independence Day celebration, which is in large part an excuse to bar-b-que meat products, blow up fireworks, and drink beer. If you’re tuning in from abroad, you are probable sober enough to read Daniel’s upcoming post on gravitational waves. For the rest of the drunken US crew, you can probably handle the Muppets.

PS. While we’re talking beer, I must recommend the current Full Sail Limited Edition L.T.D. (Recipe No. 3), sold in bottles with the pale blue label. Seriously. Try some.

(h/t: Again with the CakeWrecks)

We present an analysis of Conficker Variant C, which emerged on the Internet at roughly 6 p.m. (PST) on 4 March 2009. This variant incorporates significant new functionality, including a new domain generation algorithm and a new peer-to-peer file sharing service. Absent from our discussion has been any reference to the well-known attack propagation vectors (RCP buffer overflow, USB, and NetBios Scans) that have allowed C’s predecessors to saturate so much of the Internet. Although not present in C, these attack propagation services are but one peer upload away from any C infected host, and may appear at any time. C is, in fact, a robust and secure distribution utility for distributing malicious content and binaries to millions of computers across the Internet. This utility incorporates a potent arsenal of methods to defend itself from security products, updates, and diagnosis tools. It further demonstrates the rapid development pace at which Conficker’s authors are maintaining their current foothold on a large number of Internet-connected hosts. Further, if organized into a coordinated offensive weapon, this multimillion-node botnet poses a serious and dire threat to the Internet.

Yikes! Whoever wrote this thing is not a very nice person…or persons. The C variant apparently managed to upgrade itself over the network, and disables security anti-virus software. If I were you (and I am apparently not because I use only OS X and Unix) I would update my antivirus software every day and scan my machine. And leave it off next Wednesday if possible.

Pass the word…

Troy writes:

“I’m a high school math teacher who is trying to assemble an extra-credit reading list. I want to give my students (ages 16-18) the opportunity/motivation to learn about stimulating mathematical ideas that fall outside of the curriculum I’m bound to teach. I already do this somewhat with special lessons given throughout the year, but I would like my students to explore a particular concept in depth. I am looking for books that are well-written, engaging, and accessible to someone who doesn’t have a lot of college-level mathematical training. I already have a handful of books on my list, but I want my students to be able to choose from a variety of topics. Many thanks for all suggestions!”

There are some good suggestions in the comments, and some not so good ones. Surely our wise and mathematically sophisticated readers will be able to help. Add what you can there, and in the comments here if you like.

As you can see, the top three themes are “research”, “project”, and “work” indicating that the letters are highly weighted towards what students have actually accomplished, rather than just pure intellectual firepower. The cloud for graduate students applying to postdoctoral positions would be more biased towards words like “thesis” and “papers”, but would again emphasize what one has done, not how intelligent one is.

So, if you are a student thinking about graduate school, you should make sure you get involved in research, and, when you do, make sure you get something done!

• “I’m sure Stu Dent could do well in graduate school, provided you can get him to talk to you more than I ever could.”

• Transcripts with three times the number of courses (and substantially better grades) in music than in physics.

• Deep, Meaningful quotes from rock bands and dead hip-hop artists in the footer of the applicant’s cover letter.

• “No other institution would benefit more from my presence than yours.”

• “I only want to work on Topic X! Nothing is cooler than Topic X! My intellectual life is a shrine to Topic X.” Except, our department has no relevant work on Topic X.

• “Stu Dent has excellent physical intuition and will undoubtedly succeed in graduate school”. Except, Stu has mostly B’s and C’s in their physics courses and a 15th percentile on the physics GRE.

• Students who have taken no math beyond calculus.

Here, we’re not telling you how to get a postdoc; we’re presuming you already have more than one offer in hand, and need to choose between them. (Yay you!) At some point we should write about applying for postdocs, but that season is largely passed. Note that postdoc situations vary wildly from field to field, and my experience is largely in theoretical physics; there is more advice at Dr. Isis’s place, and I’m sure elsewhere — as usual, leave links in the comments. Free advice on the internet is worth what you pay for it, but if you get a variety of different perspectives a nugget of wisdom might sneak through.

To decide which postdoc position is right for you, it makes sense to think about what your goals are in being a postdoc in the first place. Generally they look something like this:

1) Do some good science.

2) Learn new things and grow as a scientist.

3) Put yourself in a good position to land a faculty job.

The very good news is that these goals are not in conflict! You can do good science while learning new things, and you can do both of those while positioning yourself to apply for faculty jobs. Indeed, you’ll be in much better position (obviously) if you have done some good science. However, it’s possible to do some good science and nevertheless end up in not such a good position.

Before we unpack that, we should say a word about other considerations. You might care about geographic location, or proximity to a loved one, or easy access to jazz or martinis or gambling or whatever your favorite vice may be. (Personally, I can’t decide.) I’m all about the other considerations, and would never tell you to discount them. Life is short, and the years you spend as a postdoc are just as truly years of your life as any other years. However … if you were thinking that it would be worthwhile, at some point in your life, to sacrifice on your other considerations for a bit in order to concentrate on doing the best science you can — now is the time! Of all the hurdles and bottlenecks along an academic career path, the jump from postdoc to faculty is probably the hardest, just in terms of raw probabilities. (There are a lot fewer faculty jobs than there are postdocs looking for them.) At the same time, the transition from the comforting embrace of graduate school, where (at least in principle) you have an advisor looking over you, to the naked Hobbesian individualism of being a postdoc, where your personal initiative counts for everything, can benefit from a certain amount of increased focus. I know, “comforting embrace” isn’t the first phrase that comes to mind when you think of graduate school. But there is more structure there, and a sense of belonging to something bigger. (Often, as a postdoc, the department won’t even list you in any sort of directory.) So, while there’s nothing wrong with taking other considerations seriously, this temporary phase of your academic trajectory is arguably the best time to put those on the back burner while you concentrate on your job, hoping that sacrifice will pay off later. How much you balance those competing considerations is up to you.

(The extent to which personal initiative counts varies wildly from academic field to field; in a big lab, the role of a postdoc may be little different from that of an advanced grad student. For theorists, the role of a postdoc is little different from that of a beginning professor — you are expected to come up with your own ideas and carry them to fruition.)

With all that throat-clearing out of the way, let’s tackle those above goals. First, you want to choose a postdoc position that will help you do good science. This criterion is actually relatively straightforward, but there are some subtleties. Of course it will help if you go to a place that is chock full of good scientists doing the kind of science you would like to be doing yourself. But you still have to ask some of the same kind of questions you asked when choosing a grad school — at the most basic level, would you yourself be able to productively work with these people? Do you like them, are they supportive? What do the other postdocs who are currently there — or even better, were there recently and have moved on — think about the experience?

Here is an excellent little diagnostic. Of the different places you are considering, have a look at some of the papers they have written over the last three years. Now ask yourself: which of those papers would I have been most pleased to be a co-author on? That’s a direct way of separating vague feelings that “this place is good” from “they are doing what I want to do.” But then, to kick it up a notch, look again at those papers, and in particular at the author lists. Are there any postdocs there? Is this the kind of place where the postdocs collaborate frequently and directly with the faculty and each other, or are they more on their own, or have they still collaborating with their old groups from grad school? Different departments have different personalities, but the evidence of how postdocs generally fit in should be easy to gather.

Next, you want to learn and grow as a scientist. This one is a bit trickier. You definitely do want to grow — it’s unlikely that, as a grad student, you did enough different kinds of work that you would be happy to stay confined within those disciplinary boundaries for the rest of your life. Your postdoc years are a great chance to define yourself (see below), so you should think long and hard about how you want to be defined. On the other hand, it is possible to grow too much. If your degree is in string theory, and your first postdoc is in molecular biology, and your second postdoc is in inorganic chemistry, you’re sort of just being incoherent. You’ll have fun along the way — and if that’s your goal, that’s great — but if you are planning on moving to the next level, you want to be broad without losing coherence entirely. You want to challenge yourself with new things, but you want to challenge yourself productively. You certainly don’t want to think of your postdoc as another round of grad school, where you start from scratch. You are now a professional scientist with some established expertise, and you would like to build on that expertise.

But at the same time — and here’s the crucially important part — you don’t want to just repeat yourself. That’s why everyone always tells you to go somewhere else for your postdoc, not to stick around the same place you were a grad student. It sounds like good, solid advice, but when the moment of decision comes, far too many people choose to play it safe, and either stay where they are (if that option is available) or move over to some group with whom they were already collaborating. It’s hard to appreciate until you’ve been around the block a few times, but different departments are truly different in their approach to doing science. One of the absolute best features of the postdoc system (and there are a lot of crappy features) is that you get an invaluable opportunity to be exposed to the idiosyncrasies and habits of mind of a completely different set of senior researchers. That can be a truly eye-opening experience, and you should try as hard as you can to take advantage. Find people with whom you can work and be productive (you want to write papers, not just take classes or sit at the feet of masters), but who will challenge your preconceptions and open your eyes to new ways of thinking about your field.

Finally we have the money goal: you’d like to put yourself in good position to land a faculty job. (That’s what we’re assuming, anyway; if not, standard disclaimers apply.) Of course this is as much art as science, and there’s a tremendous amount of noise in the system — but you control what you can.

With that in mind, recall that our advice for being a good grad student was to “Be the kind of grad student that people would like to hire as a postdoc.” Guess what? As a postdoc, you will strive to be the kind of postdoc that people would like to hire as an assistant professor. And what kind is that? If you’re honest with yourself, you can probably hit upon the right answer by contemplating the kind of applicant you would be most likely to hire, if you were already a faculty member sitting on a hiring committee. The basic rule is that you’re not going to get hired as a faculty member by being talented and smart; you’re going to be hired because the department sees that you are doing awesome things. When people hire postdocs, the applicants are still charmingly unformed as mature scientists, and their letters of recommendation will often weigh more than their lists of publications. But when it comes to hiring a faculty member, it’s rarely done purely on promise — they want to see that you’ve done something.

So when you’re choosing which postdoc to take, choose the one that maximizes your chances of actually doing something. Writing papers, and (more importantly) writing good papers. And (most importantly) by “good” we do not mean “technically competent.” We mean interesting, even to people outside your immediate circle of friends. Papers you would want to read, even if you hadn’t written them. Those are the kinds of papers you want to be writing as a grad student.

The need to write interesting papers should be obvious, but sometimes it gets lost in the excitement. Writing papers as a grad student can be like having sex as a teenager — you’re amazed that it’s happening at all, and not so concerned with excelling. But at some point, as you mature, it becomes important to do it well. It is deadly, as a postdoc, to fall into the trap of writing papers just because you can write them. Like it or not, there are many people like you competing for a scarce resource in the form of faculty jobs. You have to distinguish yourself. If you are working within any field where there is a nontrivial chance of getting hired as a faculty member, there will certainly be other people writing papers in the same field. What is it that will make your papers better?

And it’s not only good papers — it’s papers that define who you are. That’s a question you will literally be asked when you are applying for faculty jobs — what are you really? What do you do? And the appropriate answer has to be well-defined (like it or not) in terms that are comprehensible to a faculty hiring committee. “I work on models of dark energy” is a bit narrow; “I am a theoretical physicist” is a bit broad; “I work on field theory and particle physics applied to cosmology” is about right. (You can always, and in fact should, continue to broaden your scope all throughout your career.) But you can’t just proclaim it; your list of publications has to proclaim it for you. You won’t want to work on the same thing over and over again, but you do want the work you do to tell a coherent story. Each paper is a dot on a map of possible problems one could be thinking about, and you want your set of dots to form a sensible picture. A postdoc period is a good time to fill in what you might think of as gaps in your toolbox, if you will excuse a terribly mixed metaphor. Become the scientist you would want to hire.

Figure all that out, and then choose the postdoc position that will maximize your chance of writing the papers that make it happen. Easier said than done, I know. If it were easy, it wouldn’t be any fun, would it?