This workshop is intended for PhD students and postdocs who want to learn and share with their peers new advanced techniques in data analysis and apply them to complex neural datasets. During the workshop, attendees will present their research projects, followed by a hands-on programming tutorial on the computational techniques used in their work. The purpose is to gain detailed understanding of the complexity of data and of the appropriateness of the different analysis techniques. The ideal participants are theoreticians with experience in analyzing experimental data as well as computationally minded experimentalists. By mixing a group of scientists with diverse background but with overlapping goals of uncovering structure in neural data, the participants will learn an array of techniques and foster fruitful collaborations.
The workshop will include presentations, tutorial sessions and lots of time and space for unfiltered in-depth discussions and data hacking sessions. We envision tutorials both on advanced data analysis as well as on specific experimental techniques and data processing. Participants are therefore expected to contribute with code or data to share and a reasonable dose of energy for giving tutorials on their work. Data and/or code can come in any format, including artificially generated data, but we encourage to make them available in a form that everyone can explore them with minimal overhead. Any data is shared only within the workshop.
In order to foster an interactive atmosphere and allow everyone to give a detailed description and tutorial of their work, the workshops will be limited to a small group of participants. Participants will be provided funds to cover travel, accommodations, and meals.
We encourage applications from female scientists and those belonging to underrepresented minorities.