NeuroHackademy

Summer School in Neuroimaging and Data Science

University of Washington eScience Institute

July 30th - August 10th, 2018

About NeuroHackademy

NeuroHackademy is an annual summer institute in neuroimaging and data science, held at the University of Washington eScience Institute. The institute brings together 60 early-career participants from a range of scientific backgrounds for a dynamic 2-week course of talks, tutorials, break-out periods, and collaborative hacking sessions. Participants will gain hands-on experience with technologies used to analyze human neuroscience data, develop the ability to conduct reproducible, shareable analysis workflows, and work collaboratively on a diverse array of data analysis, software development, and other projects. The course is led by a faculty of nearly 20 leading experts in neuroscience, informatics, and data science.

Instructors

Institute faculty at Neurohackademy come from diverse backgrounds and have expertise in a wide range of fields, including neuroimaging, neuroinformatics, machine learning, statistics, data science, and neuroethics, among others. The format of the course is highly interactive and deliberately non-hierarchical; in addition to conventional lectures and tutorials, participants will have many opportunities to engage with instructors in a collaborative project development context.
Ariel Rokem (Director)
eScience Institute
University of Washington
Tal Yarkoni (Co-Director)
Department of Psychology
University of Texas at Austin
Deanna Barch
Department of Psychological and Brain Sciences
Washington University in St. Louis
Bing Brunton
Department of Biology
University of Washington
Cameron Craddock
Diagnostic Medicine
University of Texas at Austin
Eva Dyer
Department of Biomechanical Engineering
Georgia Tech
Satra Ghosh
McGovern Institute for Brain Research
MIT
Chris Gorgolewski
Department of Psychology
Stanford University
Anisha Keshavan
eScience Institute
University of Washington
Eran Klein
Department of Philosophy
University of Washington
Fernando Perez
Department of Statistics
University of California Berkeley
Russell Poldrack
Department of Psychology
Stanford University
JB Poline
Neurology and Neurosurgery
McGill University
Jake Vanderplas
eScience Institute
University of Washington
Gael Varoquaux
Neurospin
INRIA
Tor Wager
Department of Psychology & Neuroscience
University of Colorado Boulder
Kirstie Whitaker
Turing Institute

Applications for 2018 are now open!

Application deadline: March 19th, 2018

Apply

Frequently Asked Questions

Who is Neurohackademy for?

There's no single answer to this; in the past, Neurohackademy (formerly Neurohackweek) has attracted applicants and participants from a wide range of backgrounds, career stages, and skill levels. In general, however, our prototypical participant is an early-career researcher--most commonly a mid-to-late stage graduate student or early postdoc--who has some prior experience analyzing neuroscience data, as well as basic computational literacy (including minimal familiarity with basic programming concepts). On the spectrum of the many training courses out there, Neurohackweek fits somewhere between beginner courses and advanced courses. We assume a basic familiarity with core concepts in both neuroscience and computational science, but we also give priority to applicants who do not have strong expertise in both domains. If you don't know what a for-loop is, you'll probably get more out of an introductory course like Software Carpentry. Conversely, if your full-time job is developing state-of-the-art machine learning algorithms for joint EEG/fMRI-based clinical prediction, this probably isn't the right course for you either. But if you fall somewhere in between these extremes, congratulations--you're our target audience!

We also strongly encourage members of groups that are underrepresented in science to apply. Diversity is one of our explicit evaluation criteria, and we work hard to try and make Neurohackademy a comfortable and welcoming environment for people of all races, genders, orientations, nationalities, and other backgrounds.

I'm an early-career researcher with a strong background in a computational field, but little or no experience in neuroscience. Can I attend?

While we don't expect most applicants to have a very strong background in neuroscience, we do impose a soft requirement that applicants should have at least some prior experience working with neuroscience data. It's important for us to make sure that participants with computational backgrounds are confident they'll enjoy working on neuroscience problems during (and ideally beyond) the course, and have sufficient familiarity with basic neuroscience concepts to benefit from the materials and projects. So if you have a background in, say, physics or computer science, but have never touched a neuroscience dataset, this probably isn't the right course for you. If, on the other hand, you've had some prior experience (possibly in a collaborative context) working with neuroscience data (e.g., you've helped write algorithms to process or analyze brain data), and enjoyed it, you should absolutely apply.

I'm an early-career researcher with a strong background in neuroscience, but my computational skills aren't very strong. Can I attend?

The primary goal of Neurohackademy is to help researchers develop the computational skills they need in order to make the most of large, rich neuroscience datasets. So we certainly don't expect applicants to come in with extensive prior programming experience (and if anything, that might hurt one's chances of admission, since there's no point in us trying to teaching someone things they already know!). That said, we do assume that all participants have a minimal level of programming competency--without which a participant will probably find it much more difficult to benefit from the course.

This of course leaves open the question of what we mean by "a minimal level of programming competency". The short answer is that you should be comfortable writing a simple analysis script (in a language of your choice) that uses basic control structures (i.e., if-then statements and for-loops). Beyond that, things get murky. In our experience, many beginning programmers (and also many non-beginners!) are not very good at objectively assessing how much they actually know. So if you're on the fence, we strongly encourage you to go ahead and apply anyway.

I'm a [faculty member/research assistant/postdoc/1st year graduate student/...]; can I still apply?

Applicants at all career stages are welcome to apply to Neurohackademy. In the past, we've admitted participants who range in experience from research assistant all the way through tenured full professor. We don't consider career stage as an explicit factor in the evaluation process. That said, the admission criteria do implicitly give some preference to graduate students and postdocs, as applicants at these career stages are most likely to benefit from the course (undergrads and research assistant are less likely to have had time to develop the necessary basic computational and/or neuroscience skills, whereas current faculty typically have less opportunity to directly apply any skills they might gain). Our application process shouldn't take more than an hour or two of your time though, so if you think you'll benefit from the course, we encourage you to apply regardless of your career stage.

I want to attend Neurohackademy, but I can't afford it. Is there travel support?

To make Neurohackademy as inclusive as possible, we've tried to cover most of the costs associated with attending the course. For the duration of the course, all participants will be provided with a (shared) room in the UW dorms, as well as a meal card that covers all-you-can-eat breakfast and lunch at the cafeteria. We will also provide dinner at receptions at the beginning and end of the course. Participants are only responsible for (a) travel to the UW campus in Seattle, (b) a $200 registration fee, and (c) dinner on most nights. Our hope is that this will make the course affordable to nearly all admitted participants.

That said, we recognize that some participants--particularly those traveling from other countries, or whose home labs or institutions lack funding for travel--may not be able to meet these requirements. We will therefore do our best to provide fee waivers and/or travel support to any participants who can demonstrate a valid need. To apply for travel support, please follow the instructions in the application form. You will need to arrange to have your supervisor (or department chair, etc.) email us a letter affirming that there are no local resources available to support your participation. We must receive this letter no later than 1 week after notification of admission to the institute (but we encourage you to arrange to have it sent at the same time as your application).

Note that all travel support is need-based, and plays no role in the application evaluation or decision process. We will neither privilege nor penalize applicants who indicate that they are likely to need travel funds.

Contact

Questions? Contact us!

arokem@uw.edu