[Comp-neuro] Postdoc: statistical modeling of neural data, Columbia

liam at stat.columbia.edu liam at stat.columbia.edu
Tue Aug 26 22:27:44 CEST 2008

Hi all - apologies for the cross-posting.

A full-time postdoctoral position is available immediately in the lab of 
Liam Paninski, working on statistical analysis and modeling of neural 
data, in close cooperation with our experimental collaborators.

Full information (including related publications) available here:

Current projects include the analysis of large-scale multineuronal coding 
in retina and cortex, optimal stimulus design for sensory neuroscience 
experiments, optimal decoding of neural spike train data, and analysis of 
biophysical dynamics given calcium- and voltage-sensitive imaging data.

Requirements: The work is highly interdisciplinary, and applicants must 
have strong mathematical and computational skills. Preferred educational 
background is a PhD in Electrical Engineering, Statistics, Machine 
Learning, Physics, Applied Mathematics, or Computational Neuroscience. 
Previous experience with signal processing (including sequential Monte 
Carlo / particle filtering methods), statistical modeling, and/or 
computational neuroscience is required.

Environment: The Paninski group is at Columbia University, based in the 
Statistics department and closely integrated with the Center for 
Theoretical Neuroscience, in the great city of New York.

Applicants should send email to "liam at stat columbia edu" providing:

1. a one-page description of past research experience
2. a one-page description of future research interests and goals
3. a resume of educational and research experience, including publications
4. names of at least two people that could provide letters of reference

All materials should be in Acrobat (pdf) or plain text (no microsoft, 
please), and may be included as a URL, or as an email attachment.


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