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data science

081: Data Science Will Accelerate Your Research – with Joel Schwartz, PhD

As a graduate student, Joel Schwartz developed an immunofluorescence assay for neurotransmitter transport. To quantify his results, he needed to circle the cells in each image so the computer could measure the intensity.

By the time he graduated, Joel had circled over 10 million individual cells.

Over the years, Joel discovered a better way: he taught computers to do the repetitive, complex, and confounding parts of data analysis.

And now he trains other scientists to do the same.

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080: Postdoc Straight Talk – Where Are They Now?

Uncertainty is a defining feature of postdoctoral training:

  • Q: Is a postdoc a student or an employee? (A: Neither. Both?)
  • Q: Should you continue in your PhD research field, or try something new?  (A: Yes)
  • Q: How are you supposed to find a job while you’re ALSO doing research and writing papers? (A: Pray that the Career-Fairy leaves one under your lab notebook while you’re at seminar.)
  • Q: How long should a postdoctoral fellowship take? (A: Now you’re just being mean!)

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079: The Insider’s Guide to Industry – with Randall Ribaudo, PhD

If you’re an academic scientist, applying for an industry job is a bit like traveling to a foreign country.

First, there is paperwork.

Will they accept your Curriculum Vitae as is, or do you need to crunch it down into a résumé? And how on earth do you get through the screening software that filters through the 1000+ applications?

Next, there’s the language barrier.

You’ll need to communicate your qualifications in an interview that may last just a few minutes.  You might describe a key experiment you designed with six controls and twelve replicates, but what the interviewer needs to hear is that you have experience in ‘quality control and quality assurance.’ Don’t expect them to make the translation.

Last, there can be culture shock when you actually get the job and start to work. There are aspects of your academic training that you will need to un-learn if you want to be successful. You can either begin the job with a sensitivity to these new cultural norms, or you can learn them the hard way…

This week, we talk with a scientist who acts as travel guide for academics who want to make the leap into industry.

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078: Knowing When to Leave Academia – Feat. The Recovering Academic Podcast

Maybe you’re in love with science, but you just can’t imagine your life as a PI.  And maybe you’ve had a string of experiments fail and you’re just ready to put the entire ‘lab thing’ behind you.

You have a choice – you could leave academia and try to find your way in industry, publishing or some other career. Or you could try to revive your research in the hope that lab life will eventually improve.

But how do you know which choice is right for you?

What happens if you make a mistake?

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077: Google Discovers Five Keys to a Productive Lab

Google is data-obsessed, so it should come as no surprise that the company sought to apply its analytical expertise inside the organization.

In an endeavor dubbed “Project Aristotle,” Google sought to answer a vexing question: What factors are important for a successful, productive team?

Their findings may have profound impacts not just at Google, but in a lab near you…

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