New school year, new contributor!

This blog started as a collaborative effort. As we all advanced in our careers and grown families some regular contributors have become irregular contributors, and I have been the primary curator for sometime.

UNTIL NOW!

Sara Wilbur reached out asking to write a guest post. We worked on getting her delightful post out together.

And with the new school year, she’s back for more! She’ll be writing about artic squirrels and telomeres and quirky scientists and life in Alaska.

And I’m thrilled that’ll she’ll be posting on Thursdays. Welcome to the NiB family!

 

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In 1974, They Gave The Nobel To Her Supervisor. Now She’s Won A $3 Million Prize

One of the great misconceptions of science is that great discoveries start with a “Eureka!”.

More often than not, great discoveries start instead with a “that’s funny/odd/strange, I wonder what’s going on here”. And that’s what happened to Bell Burnell. She and her graduate supervisor, Antony Hewish, built a radio telescope to observe strange objects in distant galaxies known as quasars. It printed the data as a line (using red ink) across ~100 feet of paper per day. And in pouring over that data, Bell noticed something strange: “an unclassifiable squiggle”

The squiggle was soon identified as pulsars, rapidly spinning neutron stars that emit radiation. Finding them is considered one of the greatest astronomical discoveries of the 20th century. So much so that it won a Nobel Prize… for Bell’s advisor.

However, she gets the last laugh: 50 years after the “unclassified squiggle” in red ink, her discovery has earned her a Special Breakthrough Prize in Fundamental Physics, which comes with a check for $3 million. Dr. Burnell is donating her prize winnings to the U.K.’s Institute of Physics, where they will fund graduate scholarships for people from under-represented groups to study physics.

“I don’t want or need the money myself and it seemed to me that this was perhaps the best use I could put to it,” she told the BBC, adding that she wants to use the money to counter the “unconscious bias” that she says happens in physics research jobs.

The astrophysicist noted there has been an upside to the Nobel snub all those years ago.

“I feel I’ve done very well out of not getting a Nobel prize,” she told the Guardian. “If you get a Nobel prize you have this fantastic week and then nobody gives you anything else. If you don’t get a Nobel prize you get everything that moves. Almost every year there’s been some sort of party because I’ve got another award. That’s much more fun.”

Read the full story here.

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Getting into industry: LinkedIn Profile

This post continues my discussion about academia to industry, and how I got from there to here. 

I made the decision to get a job in industry, and was immediately faced with the task of: “Ok, now how do I do that?” And the sad truth is that it’s entirely different than academia.

You need people to be able to find you from the sea of other options/people. You then need them to want to talk to you. And only then, at the interview, is the job won or lost. So we’ll start where I started, putting yourself into the ether of the job market and making yourself known. And you start by developing a LinkedIn profile.

I know a few academics have a profile, but most people in academia haven’t taken it too seriously. But recruiters and employers really do look at them. And building a good one is non-trivial.

Pick a professional photo for your profile picture. Not a photo of you pulling frogs from your experimental ponds, or pipetting like a pro (unless you’re applying for a laboratory role). Get a headshot of you looking smart and professional. And if you don’t have one, have one taken. Pay for it. It’s your first foot forward, and it’s worth the investment.

Write a “personal statement”. This should all be visible without someone having to expand the “more” tab. Make it catchy and easy to understand. “I’m a scientist passionate about making data driven decisions”. Or “I have spent a career focused on increasing understanding of statistics”

Next, list all your jobs. Include your PhD and MS and postdoc positions.  No need to go back before then, no one cares that you worked at McDonald’s in high school. (However, if you had significant work experience before or during your academic journey, consider whether the position might be relevant to include, especially if it involved related analytic work or was a management position.)  Under each position, list what you did in that position. This is remarkably similar to the academic PhD. Now, go back and make all your descriptions of your jobs entirely free of jargon. Make the bullet points simple and easy to understand. Each one should be no more than 10 words. NO MORE THAN 10 WORDS. You’re not trying to sound smart here, you’re trying to get a recruiter who has no or limited knowledge of science to know that you’re worth talking to. Feel free to steal language DIRECTLY from job posts of jobs you might want. If the job post says: “need to be able to multitask in a fast paced environment” write “I am able to multitask in a fast paced environment”. Plagiarism is ok here. Get used to this, you’re going to do it in a few different steps in the getting a job process.

Finally, go look at jobs you’re interested in on LinkedIn. At the bottom of each job, it says “you have X skills in common with others that are looking at this job”. Click on that and find out what skills your profile is missing. Do you have those skills too? Add them to your profile. Remember when I said it’s ok to plagiarize to some extent. When you have desired skills, you need to make sure other people – especially the job recruiters – know you do.  (NOTE:  there’s a huge difference in plagiarizing the description of the skills you have and making up a skill set you don’t have.)

Next week,  we’ll go over how to make your resume good enough that recruiters looking at you will want to talk to you.

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My current LinkedIn headshot. Photo credit to my great good friend Cat Thrasher

Moving into industry: You have most of the skills you need, and you can learn the few you are missing

Continuing on in my series about academia to industry, here’s how I gained the skills I needed to get a job outside of academia. 

I mentioned last week that I decided I wanted to leave academia, but then spent a full year preparing and learning what that meant. I started with an understanding that I had lots of skills, but wasn’t sure how those would translate to anything besides academia, and I ended with a job in industry. So I’ll start with the skills you do have that are applicable (yes, even you) and then talk about which ones you should make sure you have before starting to apply:

Skills you have:

Teaching and Presenting: One of the most critical traits desired in people who work with data is that they are able to communicate that data to other people. It is RARE in industry to have someone who can do the analyses AND communicate those to shareholders and relevant decision makers without them scratching their heads in confusion. But the good news: your entire academic career has prepared you for just this event. You know all those times you taught, and tried to get undergraduates to understand what you were talking about? Or those conferences where you build presentations to best present your results? They are training for doing that very thing which is VERY valuable in the world outside of academia. You already have this skill (high fives all around!).

Statistical knowledge: I know I sound like a jerk when I say this, but since moving into industry, I keep having to revise the list of things that I though everyone knew. I was asked “what is a p-value?” my first week, and have been asked more basic questions about statistics than I was ever asked in academia, even teaching undergraduates. You have a career full of experience doing experiments, collecting data, and making sense of that data by running statistical analyses. You are already ahead of the game in this regard.

Working hard: My mother told me: “The beginning of every job is the same, nose to the grindstone and work hard” and she was right. You need to be able to work harder and longer hours than you’re used to. Think back to your PhD – hours like that, only longer and in one place. The good news is that most of the multi-tasking you used to need to do is off your plate for now. The bad news is that means you have 9 + hours a day to focus on one task. Luckily, you’ve been doing this for awhile, and being a workaholic comes naturally to you. And even more luckily, this is not a long term commitment. You need to work hard at the beginning, but I’ve found it rare for people in my company (and other companies my friends have moved into) to work outside of regular business hours. This is a sprint, not a marathon.

Teaching yourself: In industry, they don’t expect you to be ready to go out of the box, like they often do in academia. In most industry environments, there is this whole process called “onboarding,” which I had never heard of before I started my current job. They know it’ll take you a little while to get up to speed. But, as an academic you’ve got a lifetime of experience teaching yourself. Great, it’ll serve you well. You can spend those first few months learning the things you’re going to need to know on the job, and that ability puts you ahead of your peers.

As you can see above, we’re already qualified, and have the potential to be successful. But you do need a few skills, at least for data science, that it is unlikely you have already attained. However, you can pick them up. Here are a few:

Python: Most academics I know code in R. The fancy ones also code in another language (I wrote simulations in C++)(I am not fancy though). While R is an excellent language for data analytics, and arguably the best in the world for statistics (come at me), for getting code into production, you need to know python. It’s similar to R, so shouldn’t be too hard, and if you have experience using R as a object oriented programming language, then it’ll be easier still. I learned python using DataCamp and strongly recommend it as a great resource. It has a jupyter notebook embedded in the site so you’re able to run code as you learn (learning by doing is important for me). But there are also books, youtube videos, coursera and udacity, and probably flash cards that will also help you learn this skill.

Querying database: In academia, we work on what are called “flat” data files, like CSV or excel files. Once you are looking at customer data, a flat file is simply too small. It’s like trying to open a NGS sequencing file – it’s just laughably impossible to do with your computer. So you need to learn how to query a database with schemas, like Postgres or MySQL. It’s a pretty simple programming language, and you’re going to learn to love to join tables. But this is a skill of taking a mountain of data, and finding the flower you want to study amidst the rocks. It takes time and practice, but is learnable.

Docker: I know I’m focusing a lot on the technology, but it has stood out to me as the one thing that’s very different between industry and academia. Docker is a way to run code locally that is entirely repeatable elsewhere. Your code is run within a “container” that is created with all the things you need installed in it, in a requirements file and an image. If you’re missing a requirement that exists locally on your computer, but is not in your file, the requirement won’t run. As a result, with the code base alone, you’re able to entirely reproduce your work, regardless of where you’re running your code from. When putting your work into deployment, this is especially awesome because you know that your container is ready to go before you deploy it. And it’s becoming ubiquitous across industry, so jump on that container bandwagon and download docker.

I’m sure I’m missing some things, and there are wealth of cultural differences that I haven’t even approached (feel free to comment below). But the gist of this post is that you ALREADY HAVE MOST OF THE SKILLS YOU NEED TO SUCCEED IN INDUSTRY. And the ones you lack are trival to learn. Now that we know this,next week we’ll talk  about one of the things you need to do to actually apply: a linkedIn profile.

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You’ve presented your research, you’ve taught. You know how to communicate results, you’re already ahead of the game.

To stay or to go: making the decision

In revisiting my academia to industry series, I’ve decided to write down some of the advice I’ve given in response to questions from those in academia since starting my job in industry. The scariest part of leaving academia was the venturing into the unknown. I’m going to write down things I wish I had known before starting this adventure, and you’re welcome to come along.

The first step on the journey from one career path to another is making the decision to go. Sometimes this happens organically. I have a friend whose postdoc advisor left her faculty position to help found a biotech startup, and my friend followed her from the University to the real world. Another friend who met someone at an academic conference and was offered a position in industry. These transitions happened seamlessly.

For me, it was a monumental decision that took me over a year to make, and another year to implement.

It started with an inkling, “I’m not sure I want to keep doing this.” I had started the career path towards the ivory tower with some basic understandings: I would never be wealthy, my choice of living locations would be limited, and I would work hard all the time. But I also saw some benefits in academia: I could pursue questions that I am interested in indefinitely. I could approach interesting ideas, and spend time collecting and analyzing data. I could hang out with people who are as passionate about biology as I am, indefinitely. And for a really long time that was enough. That was worth the sacrifices.

Until, gradually, it wasn’t.

When asked why I left, I have two answers: 1) death by 1000 cuts. I wanted to be able to pay off student loans, and live comfortably. I wanted to be able to work normal hours, with normal expectations of the jobs. I was really tired of being “required” to do things for which I was not being paid. And I wanted to be able to keep asking questions, and answering them with data, without having to constantly write grants begging for money. Finally, I wanted to stop worrying how we’re going to fund the lab, and paying for research out of pocket.  (I’m still paying off the costs of some of the experiments from my PhD).

And the second answer: 2) I was walking around London and realized I wanted a different life than the one I have. Hear me out. I have always been a big city girl, but through my academic career I kept moving from one small college town to another. I did my undergraduate, Masters, PhD and postdoc in relatively small cities and rural towns. I had to – I went where the job was. Where the research was. I don’t regret any of these decisions, but I was walking around one of my favorite cities in the world and I knew I wanted to be able to choose to live here. And that was the straw that broke the camel’s back. That was the final cut. I still love biology, and this summer especially, I miss the field work. But I needed a life, in addition to a job. And I wasn’t sure I would ever be able to have that in the Ivory Tower, where working more hours and for more efforts than you will ever be paid is glorified and promoted.

But I also realized in that moment that I wasn’t going to just drop everything and leave (it’s not my style). So I started planning, finished up projects, did another full field season, and prepared. I’ll write about my preparation next week, but the decision to leave came gradually and then all at once. And it’s the first step to figuring out what’s next.

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The view from our field van/home during my last field season. No regrets, about then or now.

 

Alternatively academic

Danielle is another excellent scientist that I’m happy to count as a friend. She’s smart, funny, interesting, and gives excellent advice on a wide variety of topics for which she is considered an expert. These topics include (but are not limited to): roller derby officiating, traditional cocktails, bird pheromones, and being a science boss lady. While her role is still very much an academic position, it is not a traditional position. As a result, she was happy to share her thoughts on “alternate academia”. 

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I get a lot of questions about my job, because although I am an established academic at a university, I am not a professor. My official title is Managing Director of the BEACON Center for the Study of Evolution in Action, headquartered at Michigan State University. My position is a blend of administration and research.

I am responsible for the operations of a multi-institution, multi-disciplinary NSF Science and Technology Center. We have over 600 members at 5 universities, and it is my job to ensure that all members have access to the resources they need, like cross-disciplinary training, seminars, funding opportunities, collaborators, and our annual conference. I am our primary liaison with our funder, the National Science Foundation. One of my primary responsibilities in that capacity is compiling and submitting our Annual Report, which typically runs well over 200 pages long and documents dozens of research and educational efforts, as well as our collaborations with industrial affiliates and efforts to increase diversity in STEM. I coordinate and run our annual NSF Site Visit, in which we spend a (very) full day presenting our research, education, diversity, and knowledge transfer efforts to a panel of external reviewers, who determine whether we are meeting our goals and decide whether to recommend that our funding be continued for the following year. I organize our annual BEACON Congress, a 3-day conference for our members and other interested visitors. This conference features concurrent tracks with contributed talks, member-organized symposia, workshops, and brainstorming “sandbox” sessions where people can discuss new ideas and collaborations.

These administrative activities account for about 70% of my work efforts. Most of my remaining time is spent on research. I maintain an active research program in evolutionary biology and animal behavior. I study chemical communication in songbirds, which involves both field and lab work and collaborations with chemists, microbiologists, and other evolutionary biologists. I supervise a postdoctoral researcher, and I have also served as the external member of two doctoral dissertation committees. Finally, I also do a fairly significant amount of service to the field, reviewing journal manuscripts and grant proposals and serving on NSF review panels.

How did I get here? Well, to be honest, I was initially interested in a more typical tenure-track career. I applied to well over 100 tenure-track positions over a couple of years, was invited to a handful of campus interviews, and received one job offer that did not suit my needs. After the last round of interviews, I had begun to sense that the realities of a tenure-track position did not match the career I had envisioned, and started to consider alternative paths. I was a postdoc at Indiana University at the time, and started looking around at the other researchers I admired there. I realized there were quite a few people involved in running research centers who appeared to have the perfect job, in my opinion anyway. I started thinking about looking for these kinds of opportunities, but I didn’t really know where to start.

Lucky for me, just a few weeks later, a job ad was posted on the Evol Dir listserve that seemed to be exactly what I was looking for – a brand new NSF-funded center was hiring a Managing Director. They wanted a person who was an active researcher in evolutionary biology, not a pure administrator, so that the person in this position could understand and communicate the science done at this center. I had no idea whether they would consider me even remotely qualified, but I worked harder on that job application than I ever had on any tenure-track application. I was invited to interview, and shortly afterwards they offered me the job.

It’s difficult to give advice to someone who is interested in a similar career, because there is no defined path, and there is no central resource to find jobs like mine. Often, these “alt-ac” jobs are what you make of them. I tell people to keep your eyes open and network as much as you can. If you are looking to make a career change, make sure people know about it. Graduate students are often afraid to admit that they don’t want a tenure-track job, for fear of “disappointing” their advisor. In my experience, most advisors just want their students to be successful, on whatever path they follow! Jobs like this are often not advertised as openly as mine was. If people know that you are looking for an opportunity, they will mention your name when they hear about such things. Things don’t always work out the way you think they will, and that can be for the best.

The down side of my position is that it has an end date. NSF STC funding lasts for a maximum of 10 years. We are currently in the second half of year 8. Where do I go from here? It’s too soon to know for sure, but there are a number of possibilities that interest me. At the top of my list is working for the National Science Foundation. I’ve learned a lot about how NSF works in my time here, and also through experience serving on proposal review panels. I am particularly interested in the STC program itself, as their model of facilitating collaborative “team science” is inspiring – and it’s working!

Working deeply towards a more balanced life in academia

Sara Wilbur is a second-year master’s student studying hibernation physiology at the University of Alaska Fairbanks. In her previous life, she toured the country as a violinist with a folk orchestra called Patchy Sanders. Sara recently returned to her hometown of Fairbanks to be with family and to unlock the mysteries of telomere dynamics in arctic ground squirrels. She also enjoys delicious beer, knitting, and skijoring with her husky mutt.

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Deep Work by Cal Newport was introduced to me by Dr. Kevin Winker, curator of birds at the University of Alaska Fairbanks’ Museum of the North. I took a course from him in spring 2017 called Advanced Explorations in Genomics. In our last class of the semester, Kevin recommended the book to us nine graduate students and I followed his suggestion. The central message of the book is that focused, undistracted effort devoted to mastering difficult concepts efficiently produces work of true quality and value. In it, Newport discusses the social media time sink, busyness as a mask for true productivity, and how the ability to work deeply is a valuable skill in today’s economy.

I felt so inspired by Deep Work that I interviewed Kevin late July 2017 to discuss Newport’s ideas. Kevin is a kind, thoughtful person who provides an invigorating balance of support and challenge in conversation; talking with him was a pleasure. I left our chat feeling inspired to continue honing my focused working habits.

Sara Wilbur: Can you paraphrase Cal Newport’s definition of deep work? 

Kevin Winker: Scheduled periods of intense focus on a topic of interest. [Newport] is certainly not the first to recognize the importance of regular scheduling of intense focus to achieve a refined product when tackling complex mental tasks.

SW: If he’s not the first to describe this sort of work, why now write an entire book about it? 

KW: With increased electronic access to things like social media, computers, Google, etc., our lives and our attention spans have become much more fractured and there is a cost to be paid for that. We are constantly distracted and we are always interested in the next shiny object that passes by. Those environmental effects and that fracturing cause us to lose the ability to focus intensely on a single topic. And our brains love to be distracted, they love instant gratification, and that is something that has to be fought against to enhance quantity and quality of product.

SW: On your note that we’re predisposed to distraction, what I think, and what Newport describes, is that society actually encourages distraction via the importance placed on social media, instant email responses, etc. 

KW: Absolutely. You have to have the ability to control your immersion in it. It is difficult to control how much time you spend with those distracting things. Twitter is a fantastic tool for science and for social aspects. However, there is only so much time in a day, and how, in our business, are you going to be successful in producing the product that brings that success? Rigorously holding back those distractions becomes a critical skill. And it’s really hard.

SW: Newport has a section detailing how you can fit deep work into your life no matter what your schedule, lifestyle, or career. He thinks that no matter what your obligations are there is a way to regularly fit in periods of deep work.

KW: Yes. Schedule your time and follow through. It can be tough, especially with so many distractions. One of my career’s most important papers took nearly ten years to complete because it was an incredibly complicated problem. Simply beating my head against for years wasn’t necessarily solving it. That’s a nice thing I like about multitasking projects. Having Task “A” percolating in your brain when you switch to Task “B” can be quite helpful because it’s just sitting there, stewing, and sometimes new insights can just pop into your head.

SW: Yes. Newport is a big advocate for focusing singularly on a project. However, some complex problems get solved in your unconscious. You can pop it in back there and trust that your unconscious is going to work on it even after you’ve shifted your conscious focus to another project.

One thing I really like about the book is that Newport convinces us that deep work produces work of value.

KW: Yes, and quality of work is higher. You can still produce things of value in a fractured existence. I tend to reserve things like making tables and figures for times when my brain isn’t at its best. You can also create product of quality in a more fractured existence, but not product of complex quality.

Speaking of a more fractured existence, email is potentially a bottomless sink of potentially important and unimportant communication. I try to look at it just a few times a day.

SW: That can be hard to do. You have to turn off all the little dings that let you know when something new comes in.

KW: Never use them. Never use those. Ever! The first thing you do when you pick up a new piece of software is figure out how to prevent it from badgering you.

SW: I think email is a perfect example of what Newport calls “busyness as a proxy for productivity.” I could be sending high-quality, well-written emails all day. I would be making progress in terms of my communication with colleagues, but I wouldn’t be making progress with the nuts and bolts of my research.

KW: Right. Critical to recognize that.

I’m still learning how to be more productive, and how to be a better writer. I remember sitting down, talking with Terry Chapin [Professor Emeritus, University of Alaska Fairbanks], and I said, Terry, how are you so productive? He said, well, I keep a list. I said, gee, I keep a list too! [Pulls list out of pocket]. And I said, but how do you get so many papers done? And Terry said, I always keep something of mine at the top.

And that emphasized the fact that we can be so accommodating to others that we bump our own priorities in favor of satisfying someone else’s request. Terry’s key words there are that your projects have just as much priority as anyone else’s. Since then, I’ve been unembarrassed about my priorities being equal to anyone else’s.

SW: I was recently listening to a podcast interview with Newport and he said he doesn’t let his mood affect how he works. He doesn’t let how he’s feeling compromise his preplanned work schedule. I was curious what you thought about that, and to what level this is realistic and how one can find a healthy work-life balance.

KW: I agree with him. Deep work and productivity of the kind we’ve been talking about require a very strong commitment. That time you’ve set for yourself to work on things of high priority is so precious and you can’t bump it around. Didn’t he talk about training yourself to do this kind of work?

SW: Yes, he calls it deliberate practice, [where] you’re consistently, every day, training your mind to avoid distractions and to become comfortable with boredom.

KW: I love that. I’ve become a big fan of boredom. What I do when I am in a boring situation is bring out the series of questions in my mind that I’ve been waiting to work through and use that time to solve complex problems. I now look forward to boring times!

When you schedule that time that you know is precious, and that you know enriches your life and your life’s success, and you enjoy spending it, yeah, maybe it doesn’t give you the instant gratification that Twitter and Facebook and the internet would give you, but you know it gives you long-term gratification. So, buckle up and do it. Part of that discipline, that deliberate practice, part of making that work is doing it every day. Even with one hour every day, you can move a mountain with a teaspoon. You just have to go at that thing every day, with your teaspoon. You’ll feel so good with your progress and with the amount of material you can move.

My interview with Kevin was engaging and insightful. Our discussion further convinced me that to produce work of real value, I need to dedicate regular periods of intense, focused work on tasks that will advance meaningful progress. However, I left the conversation still curious about how effective work leads to fulfillment that seeps into your non-working life. Since starting my masters in 2016, I’ve been an advocate for working smarter, rather than harder. Some part of me knew that it was possible to make progress while still having a happy life outside of the lab. However, I felt surrounded by supervisors and peers who practice unsustainable work habits. How could I be sure that it was acceptable to allow myself consistent free time in the evenings and on weekends?

I found my answer in Deep Work. Newport advocates focused, intelligent work in the office. He suggests laying your work to rest at a reasonable hour and picking it up the next morning with a fresh, relaxed mind. Interestingly, however, Kevin does not seem to heed this bit of Newport’s philosophy. I asked him if deep work constrained between 9 am and 5 pm improved his overall quality of life, and he neatly sidestepped my question before moving on to another subject. Although he values smart work while on the job, he works very long hours, works at home, and works on the weekends. Perhaps his immense time investment in his work is fulfilling in and of itself. For me, I prefer and seek a balance, and found support for this personal conviction in Deep Work.