Job Search Strategy

Over the past several months, I’ve gotten an incredibly large amount of advice about how to search and apply for jobs.  Sources include everyone from my advisor, recent faculty hires, and current postdocs to other graduate students in my position and helpful science/academia based blogs.  I’m pretty sure, that at this point, I can just do whatever I want and say that someone told me it was a good idea.

To me, this plethora of advice says one thing loud and clear: how I carry out my job search is almost entirely based on what I personally want out of it.  You know, once you get past the basics for everyone, such as writing a proper cover letter, tailoring each application to the specific job you are applying for, and knowing the difference between a resume and a cv.  So I figured I’d write this post, not to give advice, but to give an example of how I’m searching for jobs based on what I want.  You can follow my example, or use it to create a completely different strategy that fits what you want.

Here’s what’s currently defining my job search parameters:

My future career options.  PhD students have many options (including academia, industry, government labs, administration, science writing, etc…).  I’m not entirely sure what I want to do, but I know what I don’t want.  I’m not a big fan of teaching or of administrative duties – I would prefer to keep doing research.  Thus I’m focusing on positions that are research heavy and will expand my skill set.  If I look at a postdoc position, I want to be able to learn new skills that would be useful in an industry position as a data scientist.  For an industry position, I realize it is extremely difficult to make the switch back to academia, so I only look for positions with quality and meaningful research (i.e., not advertising).

My anticipated graduation date.  Oh, the impossible to pin down and forever changing timeline that is graduation.  My rather vague expectations indicate that I am currently applying at close to the earliest possible (yet reasonable) time to apply for jobs.  There are two main schools of thought on applying this early.  The first is that you need experience applying – sending out applications, interviewing, networking, etc… and to send as many applications out as possible.  I think that’s a complete waste of everyone’s time.  My theory is that, as I’m not at a point to be desperate yet, I only send out applications to positions that are pretty much perfect for me.  No, not pretty much, perfectly perfect.  This way I don’t spend too much time applying while I’m trying to write my dissertation.  The applications I do send out I’m excited about, and I have the time to do them right.  I won’t have the regret of passing up on a perfect opportunity, and it’s not as devastating when I don’t get it, as I know still have time to find something else just as good.

Once I get closer to graduating, this strategy will change.  I will start to compromise on what I want, and apply what I’ve learned from job rejections to make my application materials even better.  The closer I am to finishing my dissertation, the more time I will spend on job applications.  But, more on this when I reach that point.

Personal preference.  To me, this is one of the most important parts of defining my job search, but the hardest to justify to others (and sometimes to myself!).  It is very difficult to see a perfect-for-you position pop up, with great benefits, perfect timing, the works, and have to say no to applying because Florida is too hot.  I try to remind myself, that even if I’m happy in the perfect position for 8 hours each day, I have to deal with the location and the happiness of me and my family for the other 16 (plus weekends and holidays).  In the end, it doesn’t matter how big or small of an issue it is (for me it’s location), just figure out what personal preferences will make or break your happiness in any job, and then stick with them.

How’s this strategy working out so far?

You may be wondering if this strategy is any good at all.  Well, I haven’t done it enough to really know.  However, in the interest of transparency, and taking down imposter syndrome, I plan to post my job statistics, once I have enough to reasonably analyze.  At this point I’ve submitted 5 applications.  Two are pending, one was rejected after an interview, one was rejected because I forgot to ask if they sponsor visas (they don’t), and one was rejected because it was my first and I didn’t put in near enough effort.

I’d be interested to hear how others are approaching the post-PhD job search!  One of my grad school friends is taking a completely different tactic – she is not applying for anything, preferring to spend all her time finishing her dissertation.  Her focus is on getting a postdoc position through networking and possibly submitting a grant, not through previously funded and advertised positions.  What do you think about the difference in our strategies, and what’s your strategy for job searching?

Dealing with Mixed Layer Depth

In oceanography, there’s a very important characteristic of the ocean that we refer to as “Mixed Layer Depth”, or MLD.  It’s the depth of the surface layer of the ocean that is well mixed by surface forcing, such as wind and waves.  It essentially defines how much of the ocean is in direct contact with the atmosphere and directly affected by atmospheric processes.

It’s also a complete pain to deal with.

The image below shows a temperature profile, that is, how temperature changes with depth.  By glancing at this graph, you can see that the temperature is constant for about the first 200 or so meters near the surface.  Thus, the mixed layer depth here is about 200 meters.  If the graph had been of salinity or density instead, the same reasoning would apply – the mixed layer is the portion at the surface that is well mixed.

An ocean temperature profile, taken from

Picking out a mixed layer depth is quite simple visually, but it gets complicated analytically.  How do you define the bottom of the mixed layer?  Currently there are several methods which are more or less accurate depending on location and season.

The first basic method is known as the “threshold” method.  It’s defined as the depth at which a parameter (temperature, salinity, or density), differs from the value at the surface by a set threshold amount.  Given that not all mixed layers are 100% well mixed, the appropriate value of the threshold can differ between research studies, making it difficult to compare mixed layer depths.

The second basic method is the “gradient” method.  It’s defined as the depth at which the gradient (or change over depth) of a parameter exceeds a certain amount (or, alternately, reaches a maximum).  This method is meant to take into consideration those cases where the mixed layer isn’t 100% mixed, but it too has its limitations.

Other methods have been developed to further refine the analytical definition of mixed layer depth, making the whole issue even more complicated.  Often, it is hard to distinguish which method would be the best choice, especially when different methods give very different answers for the same data set.

I found one very rigorous method for calculating mixed layer depth, which was actually a combination of five other methods that were then analyzed to see which overlapped, and modeled to give a final mixed layer depth.  This 5 part method may be the best I’ve seen, but it is not at all practical.  The calculation takes several days at least!

And so, in my search for the best way to calculate mixed layer depth, I’ve defaulted to what others have used before me.  In most other studies conducted in the same part of the ocean I am looking at, the threshold method is most commonly used, with a small twist.  Now I calculate mixed layer depth with a threshold for temperature, and for density, and take the shallowest of the two to be the “real” mixed layer depth.

It may not be the simplest, or even the best, way.  But it is reasonable, consistent with past work, and enables me to make progress in my research.  Although, if I start looking at a different part of the world, I’m sure I’ll have to go through the whole process of deciding how to calculate mixed layer depth again.

Science in Prague: Part 2

I’m sitting in a restaurant, after finishing my last meal in Prague and reflecting on my time here.

The conference: Despite some early issues with organizing and unclear directions, not to mention last decisions, everything went really well. I was impressed by the quality of science and the scientists who presented their work. At times, I felt a bit lost among the geologists and couldn’t find anyone familiar. However, a conference of that size and scope also means there are often small and unique sessions, such as mathematics in earth science, or data science and analytics, that I was very interested in. For the most part, I stuck with oceanography, attending sessions on the southern ocean and ocean mixing, with the occasional foray into something a bit different. I have several notebook pages full of people to contact or papers to look up once I get back to my office.


Looking down on the poster session

Prague: I’ve also been reflecting a bit on my time in the city. I’ve decided that while I’m still not a fan of cities, this one isn’t too bad. The castles here are quite interesting, even though the prevalence of stone wears on the feet after a few days. It’s still too crowded for me. The streets are filled with tourists in the popular parts, the buildings are extremely close together, and it all got a bit repetitive after awhile. Despite that, I  still really enjoyed myself, which brings me to my final point.

Me: This trip ended up being a good lesson on how to be on my own. The first day or two, plus these last days on my own have been one of the few times I’ve had nothing to consult but my own wishes. In any normal situation I can find a reason for a decision that makes either my life easier, or someone else’s. Here, it was often only about what I wanted at the moment. Now that I’m at the end of my time here, I have to say that I feel more comfortable with myself and being by myself. It’s an unexpected, but welcome outcome.

Now, the real trick is remembering the excitement from the conference and translating that back to everyday work life to get more accomplished.