[Comp-neuro] Postdoc position in computational/statistical neuroscience available
memming at gmail.com
Fri Apr 24 04:32:24 CEST 2015
A full-time postdoctoral position is available in the Computational and
Theoretical Neural Information Processing Lab <http://catniplab.github.io/> at
Stony Brook University. We design statistical models and machine learning
methods specialized for neural data. We aim to understand how information
and computations are represented and implemented in the brain, both at a
single-neuron and systems level. We collaborate with experimental labs on
important problems in neuroscience, such as sensory coding and perceptual
decision-making. Current projects include inferring the latent dynamics of
a neural population in awake behaving monkeys using recorded spikes and
local field potential, and building scalable statistical models for
high-dimensional neural observations. Our lab provides a friendly and
highly collaborative environment.
Candidate must have a PhD or equivalent in neuroscience, statistics,
engineering, mathematics or a related field. Ideal candidate would be
familiar with machine learning and/or neural modeling. Prior experience in
analyzing neural data, high-dimensional data, and/or non-Gaussian time
series is a plus but not required. Good numerical programming skills and
experience with professional software development are expected.
For further information please contact I. Memming Park (
memming.park at stonybrook.edu).
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