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The countdown to ending my studies has begun, with less than a year left to finish my PhD. I'm currently very confused about whether or not going for a post-doc, considering that I have recently found out that physicists can do something outside academia. I might therefore look for a job in the private sector.

I work in a mathematical physics sub-field called quantum chaos. I have been programing in Python and Mathematica for the past 3 or 4 years. Although my research does not include data analysis, I do have some small experience in neural networks using Keras, which I believe would not be too hard to fine tune. At the end of my PhD I will have published no more than two papers, both possibly in Physical Review A (impact factor 3), but maybe one will be accepted in Physical Review Letters (impact factor 9). I will also have participated in two or three international conferences. I do speak some four or five languages.

So what? I understand that if I apply for a post-doc my achievements can be seen as standard, and I already have a CV aimed at presenting my research work. The problem is: what should I put in a CV aimed at triggering the private sector's attention? I see my work as immensely irrelevant. I understand that physicists are quick to find patterns and solve problems, but they must be employed to get a chance to show it. Are they really going to care if I add that I have experience dealing with harmonic analysis in cotangent bundles or that I have shown that a certain coherent state propagator is not actually an element of a Bargmann-Segal space? I have absolutely no experience working in any sort of industry, and the only assets I can offer are a reasonable knowledge of Python and Keras and the languages I speak. Any imaginable CV I write will probably make an employer laugh at me. Do I even have a chance here?

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This is why it's a good idea to think about these things during, or preferably before, your PhD. You're picking up skills, but how useful those skills are and how you're going to use them is a big question. Fortunately, you're not out of options, and you've probably learned more than you think. Some thoughts:

  • You should absolutely list Keras. With the amount of hype machine learning has been getting having experience with neural networks is a big deal. I'd go much more than that: list everything you know about data analysis. It doesn't matter if it's something as simple as linear regression. List it all, give details.
  • You should absolutely list Python as well. In fact, list all the programming languages you know. You don't have to be an expert in all of them because you can learn the others quickly. Are you able to read C/C++ code? Java? R? You can also list Mathematica.
  • You should absolutely list all the languages you can speak. These skills aren't easy to pick up. If you can speak Japanese for example, that might make you the only viable candidate for a company that's looking to send a consultant to a Japanese client.
  • What else did you learn in your research? Did you learn any algorithms that might have wider applications? For example, did you learn how to parallelize code? Did you learn how to use a Linux terminal? Git and Github?
  • Did you engage in science communication and / or teaching? If so definitely list this as well, since it indicates you can mentor others.

You should also visit your university's career center. They'll have experts who can help you.

EDIT: One more thing, take a look at the advertisements you're responding to before sending in a CV. Do you know any of the things they request? For example looking at one such advertisement, there's this:

  • Ability to query a SQL and/or NoSQL database efficiently

If you know how to do this, you should absolutely list it on your CV as well.

  • I did not think about these things earlier because I did my MSc and PhD without even paying attention. I wanted to learn more about nature and had never thought about leaving academia until last month - and I will probably not leave it. Your answer is, however, exactly what I needed. – QuantumBrick Jan 17 at 12:30
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""CV"" is for academia. "Resume" is for outside the ivory tower (government, McKinsey, Goldman, Google, industrial companies, etc.)

Postdoc or professor jobs will expect a "CV" which is a longer document listing all your publications, conferences attended, etc. It can often be several pages long.

The rest of the free world just expects a standard "resume" like in all the "how to write a resume" books. Instead of listing your publications, you can just say X peer reviewed papers written as a bullet point.

This is 1-2 pages even if you are 60 years old and extremely high ranked. While there will be some differences in the content, it really doesn't look that different for a CEO, secretary, industrial scientist, HR manager, or whatever. For someone under 40 (arbitrary, but my guideline), don't exceed 1 page. Right now you will maybe be straining a little to come up with bullet points of work or quasi work experience. But this will change as you progress and will be the opposite problem!

This is very, very far from a fresh novel problem (people graduating and needing to write up CV/resume). There is a HUGE amount of advice out there. Lots of books on this. Your guidance center can advise you on this also (even giving you feedback on your document itself). Also good to compare/contrast resumes (or CVs I guess) done by people currently interviewing.

P.s. It's normal at places like Google, McKinsey, Goldman, NSA, etc. that they would take an entry level Ph.D. and then have him do something different from his direct experience. (Same thing applies for chemists and engineers in more mechanical industries.) They just see you as a fresh smart face. You've cut your teeth on some topic but very unlikely to keep working in same exact subfield. (It would be great if you could for your sake and theirs, but it is really just rare from either side to find perfect matches. Employers end up going for the "good athlete" versus the skilled player. Given the physics and the programming, everyone knows you are smart and can do something.)

  • I am indeed wondering what I did that could be called "work", since for me it was "fun" all the time. Your point of view really made me a little optimistic, though. – QuantumBrick Jan 17 at 12:32
  • Some effort at "translation" may be required. This is normal when changing fields (and a move to industry is often changing field from pure research). For example consider how ex military have to write a resume to translate their experience into something someone in corporate America cares about. (Lots of great articles with advice on this.) But seriously, if you look on the Web or network or use your career center I bet you can see lots of people positioning Ph.D. physics experience in a way that is relevant to industry. – guest Jan 17 at 17:09
  • Some possible bullets (you won't have them all, but may have others, consider this a thought starter): (1) won conference award, (2) presented X times to academia, industry, etc. (3) attracted students to lab group (4) secured or assisted in securing funding (5) wrote progress reports (6) did Y peer reviewed papers (7) founded collaboration (8) developed new method/apparatus, etc. (9) taught courses (mention positive feedback and or an award if possible). ETC. – guest Jan 17 at 17:10
  • Just brainstorm and write bullets in Word. That is the good thing about nowadays versus typing before Word processors. It is very easy to edit/hone. And very easy to cut text. – guest Jan 17 at 17:10
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I see little reason, actually, to limit yourself to a single CV. You can have a comprehensive one, of course, that covers every interesting thing you've done, but you can also provide tailored CVs to particular purposes, leaving out the things that you believe to be irrelevant to a reader.

This implies, of course, that you aren't posting the CV to a general public site for everyone to see.

You need to be honest, of course, but the CV needs to include only relevant things. Those are naturally different for academia and industry. In fact, for industry, different potential employers might see different CVs depending on the work they do and whatever it is that you do that might be relevant to it.

Alternatively, you could provide, for a particular employer, a different organization of your CV, listing the most relevant things in a special section and the other stuff (or most of it) in a later section. The reader will focus on the relevant stuff, I think and will give up on the esoterica.

I was once advised by an employment counselor to not say that I held a PhD when looking for an industry position. There were no academic positions available at the time and, in industry, an MS was thought of as more valuable than a PhD.

  • I do have a MSc too, but I think being is physics it is worthless. My country's standard line of study is BA -> MSc -> PhD, the whole process taking around 10 years. Since I might leave to Europe to look for work, I think it is perfectly possible to omit the fact that I'm over-qualified. – QuantumBrick Jan 17 at 12:39
  • @QuantumBrick Don't miss out the MSc, or any previous qualifications. They tell a fuller story, and avoid mysterious gaps in your history (which employers can be suspicious of). Your new employer might have a use for something specific that you've done in a course, or even at high school. – Simon B Jan 17 at 15:24
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Your private sector CV needs to be different than your academic CV. I can give you a little insight into this. The best way to think about it is that your private CV highlights your skill set and your academic CV highlights your publications. I recently decided to accept a position in academia rather than go into industry but I still applied to both.

My resume is a page long, my CV is longer than a single page. My resume was ordered as such-

  1. education/work experience
  2. Recent examples of work
  3. technical skills (programming, analysis, etc)
  4. soft skills (spoken languages, leadership, etc)

As for what you can do with a physic phd, my friend ended up taking a job at a bank. More than one physics phd is not interested in doing 2-3 post docs before finally having the street cred for an R1 to hire them. This is especially the case when they can make nearly double (or more) going straight into industry.

  • I have friends who took post-doc positions in Machine Learning in order to build a more industry oriented CV/resume. I think a PhD in physics, together with a post-doc in ML, is definitely going to attract a lot of attention (I might copy their strategy). – QuantumBrick Jan 17 at 12:35
  • @QuantumBrick And there are plenty of ML post doc positions as well. If you are doing simulation work in physics, you have a pretty good base to make the transition. And there is a good chance you are already familiar with gradient descent. – JWH2006 Jan 17 at 13:09
  • I have been working with numerical simulation, yes. All I know about gradient descent is that, well, it's basically just the chain rule. I spent some time thinking about ensembles of weights form a statistical mechanics point of view and all my friends said "mate, don't lose too much time theorizing... This field is about getting stuff done no matter what". – QuantumBrick Jan 17 at 13:47
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    @QuantumBrick Thats a good perspective. There is a ton of low lying fruit that is more about "where can I appropriately apply this technique" rather than "how can I improve it". For example, generative adversarial neural nets (GANs) were just developed a few years ago. There is a huge field of applications for those. Currently, the best use is to know when and where an ML technique is and is not appropriate. Grab a post doc at a name-brand school (stanford, duke, MIT, etc) and you will be pretty set. – JWH2006 Jan 17 at 14:09

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