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<p><span>The DiGregorio (University </span><span>of Colorado School
of Medicine) and Kilpatrick (University of Colorado Boulder)</span><span> </span><span>laboratories
are searching for an expert in theoretical</span><span> </span><span>and
computational neuroscience</span><span> </span><span>to explore
the biological mechanism of neural population dynamics driving</span><span> </span><span>sensory-motor
transformations throughout the brain. In</span><span> </span><span>particular,
the project</span><span> </span><span>will leverage biologically
inspired artificial neural networks to explore </span><span>how</span><span> </span><span>patterns
of large-scale neural activity are shaped by synaptic</span><span> </span><span>dynamics
to</span><span> </span><span>optimize precise temporal
associations required for the fine-tuning of motor</span><span> </span><span>actions
(e.g. cerebellum) and performing Bayesian inference-</span><span>like
computations</span><span>.</span><br>
<span> </span><br>
<span>The successful candidate will benefit</span><span> </span><span>from
working in a multidisciplinary team of cellular and circuit</span><span> </span><span>neurophysiologists
generating cutting-edge data</span><span> </span><span>sets of
population recordings</span><span> </span><span>using calcium,
voltage, and neurotransmitter imaging, optogenetics, and
high-density</span><span> </span><span>single-unit recordings
using Neuropixels. The</span><span> </span><span>Department of
Physiology and</span><span> </span><span>Biophysics is highly
collaborative with several laboratories spanning many</span><span> </span><span>aspects
of sensory and motor processing. Postdoctoral</span><span> </span><span>fellows
in the DiGreogrio</span><span> </span><span>laboratory will
benefit from tight-knit collaboration within the Cerebellum and</span><span> </span><span>Motor
Control group (Christie, DiGregorio, and Person labs)</span><span> </span><span>and
with other</span><span> </span><span>systems neuroscience
laboratories within the Department (Denman, Felsen,</span><span> </span><span>Poleg-Polsky,
and Welle). The theoretical framework will be an</span><span> </span><span>extension
of</span><span> </span><span>previous work from the DiGregorio
and Kilpatrick laboratories (see references).</span><span> </span><span>In
the Applied Mathematics department at the University of Colorado</span><span> </span><span>Boulder,
fellows</span><span> </span><span>will leverage a rich and
active environment of researchers in nonlinear</span><span> </span><span>dynamics,
mathematical biology, and data science. Fellows will also
benefit</span><span> </span><span>from other ongoing
collaborations the Kilpatrick laboratory has with</span><span> </span><span>experimentalists
collecting neural and behavioral data on decision theory (Josh</span><span> </span><span>Gold,
Penn)</span><span> </span><span>and working memory (Tim
Buschman, Princeton; Paul Bays, Cambridge).</span><span> </span><span> </span><br>
<span> </span><br>
<span>Required skills</span><span>: Experience in mathematical
modeling of</span><span> </span><span>ANNs and/or PhD in
physics, mathematics, engineering, or computer science.</span><br>
<span> </span><br>
<span>How to apply:</span><span> Please send a CV and a letter of</span><span> </span><span>motivation
highlighting your qualifications and specific interests in the</span><span> </span><span>project
and laboratory to David DiGregorio</span><span> </span><span>(</span><a href="mailto:david.digregorio@cuanschutz.edu" title="mailto:david.digregorio@cuanschutz.edu" class="moz-txt-link-freetext">david.digregorio@cuanschutz.edu</a><span>).</span><br>
<span> </span><br>
<span>References:</span><br>
<span>Barri, A., M. T. Wiechert, M. Jazayeri and D. A. DiGregorio.</span><span> </span><span>Synaptic
basis of a sub-second representation of time in a</span><span> </span><span>neural
circuit model</span><span>. </span><span>Nat Comm</span><span>,</span><span> </span><span>13:7902
doi: 10.1038/s41467-022-35395-y (2022)</span></p>
<p>ZP Kilpatrick. Synaptic mechanisms of interference in working
memory Sci. Rep. 8 (2018) 7879.</p>
<p>N Krishnan, DB Poll, and ZP Kilpatrick. Synaptic efficacy shapes
resource limitations in working memory J Comput. Neurosci. 44
(2018) pp. 273-295.</p>
<div>A Veliz-Cuba, HZ Shouval, K Josić, ZP Kilpatrick. Networks that
learn the precise timing of event sequences. J Comput. Neurosci.
39 (2015) pp. 235-254.</div>
<div>Chabrol, F.P., Arenz, A., Weichert, M.T., Margrie, T.W. and
DiGregorio, D.A. Synaptic diversity enables temporal coding of
coincident multisensory inputs in single neurons. Nat Neuro.
18(5):718-27. doi: 10.1038/nn.3974 (2015).</div>
<br>
<br>
------------------------------<br>
Zachary Kilpatrick<br>
University of Colorado<br>
Boulder CO<br>
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