Call for Applicants
Applications are closed, but you can tune in remotely!
We no longer have space for people to join us at the event, but we are excited to announce that we'll be live-streaming the entire workshop and will be providing free access to all workshop materials. Keep an eye on our website over the next week for more details: http://www.dataonthemind.org/2017-workshop/live-stream
Tackling the new data frontier
Big data and naturally occurring datasets (NODS) are increasingly of interest to cognitive scientists and psychologists. With the proper tools and mindset, these data can provide compelling evidence of human behavioral, cognitive, and social process in natural settings. Big data and NODS present an unprecedented opportunity to explore theory-driven questions -- questions rooted in theories developed in rigorous lab studies -- in real-word datasets. These naturalistic explorations can generate new ideas that can be further refined in follow-up lab studies, creating a virtuous cycle of theory development.
However, along with this unique opportunity comes unique challenges. Graduate students and postdoctoral researchers in cognitive science and psychology have often been trained to collect and handle data that are relatively small and that come from tightly controlled lab settings. Although early-career scientists have deep theoretical knowledge of their research areas that would be powerfully applied to big data and NODS, many lack experience dealing with the challenges posed by these messier (and often exponentially larger) datasets, including analysis selection, computational capacity, and data collection.
Our (free) 2017 workshop
To help cognitive scientists and psychologists tackle these issues, Data on the Mind has been funded by the Estes Fund to create a 4-day workshop of hands-on introductions to topics that are essential for theory-driven research using big data and NODS. Each tutorial is taught by an expert in that area and will include real code and other exercises that will empower participants to immediately apply these techniques to their own research.
We'll be holding our workshop during June 26-29, 2017, in the bright collaborative space of the Berkeley Institute for Data Science in the historic Doe Library at the University of California, Berkeley.
To make the event more affordable and accessible, there will be no cost to attend for accepted participants, and breakfast and lunch will be provided for accepted participants each day of the workshop. Lodging will be provided for at least the nights of June 26, 27, and 28 (note that this does not currently include the night after the last day of the workshop). More information on lodging, food, and travel can be found here.
Scope of the workshop
This workshop will rely on programming in both R and Python, and tutorials will assume that all participants will start out with at least a beginner's level of programming in both languages. We anticipate that all tutorials should be accessible to anyone with a beginner's level of programming in R and Python. Check out our list of tutorials (including abstracts and instructors) here.
Although we will consider applicants without experience at the time of application, we will not be covering any introductions to basic programming in our workshop, so we request that any accepted participants without experience in R and/or Python to complete basic tutorials before attending. We link to some free online basic programming tutorials here.
Applying to the workshop
While we're especially interested in helping early-career scientists in academia (particularly graduate students and postdocs), we welcome applications from researchers of all career stages and career paths. We especially encourage members of any underrepresented groups in cognitive science and psychology to apply.
We welcome all interested applicants to apply by May 22 using our Google Form. Notifications will be sent out by May 25.
Late applications will be considered if we have spaces remaining.