pillow lab @ princeton

neural coding & computation group

Postdoctoral position in Computational Neuroscience

A postdoctoral position in computational and statistical neuroscience is available in the lab of Jonathan Pillow at Princeton University. Our lab's research focuses on the statistical modeling of neural data and of information processing in neural populations. We develop new models and inference methods, and collaborate with a variety of experimental labs to understand how neurons work together to process information in different brain areas. Current research projects include:

- latent dynamical models of neural population activity
- statistical methods for high-dimensional data (fMRI, spike sorting, Ca-imaging)
- active learning methods for adaptive closed-loop experiments
- models of information processing during sensory decision-making
The Pillow lab is located in the Princeton Neuroscience Institute, and is affiliated with the Center for Statistics and Machine Learning and the department of Psychology. Princeton has a rapidly growing neuroscience community, with faculty who use imaging, electrophysiology, behavioral, and machine learning techniques to study the brain. Princeton has excellent programs in mathematics, engineering, operations research, computer science, and quantitative biology.

To Apply
Applicants should have a Ph.D. in a quantitative discipline (eg, Neuroscience, Engineering, Computer Science, Statistics, Mathematics, Physics) by the time they start the position. Desired qualifications include familiarity with Bayesian statistical methods and/or probabilistic models of neural data, and experience with programming in Matlab or Python. Applicants should have creativity, independence, enthusiasm for research, and a high level of expertise in math and statistics.

Applicants should submit:
(1) 1-2 page research statement
(2) a current CV
(3) the names and contact details of 2-3 references

Inquiries and applications may be addressed by email to Jonathan Pillow (pillow@princeton.edu).

Application review will begin in September 2016 and continue until the position is filled.