Connectionists: Two postdoc positions in theoretical neuroscience and nonlinear time-series analysis

[Hideaki Shimazaki]

*Call for postdoctoral researcher**s*



Two postdoc positions are available in (A) theoretical neuroscience and (B)
nonlinear time-series analysis/control (or active inference) under the
supervision of Prof. Hideaki Shimazaki.


*(A) Theoretical Neuroscience*

We've been constructing statistical analysis methods for neural data to
test theoretical hypotheses on the information coding, underlying circuitry
mechanisms, and principles of adaptation in the brain (e.g., Bayesian brain
hypothesis, predictive coding, free energy principles). We use methods in
statistical physics and machine learning. See references below for our
theoretical approaches to analyzing the dynamics of a neural population. We
are looking for a postdoc interested in conducting theoretical studies
while working closely with neuronal spiking and/or omics data.



The contract is yearly-basis and renewable *until March 31, 2026*.

Workplace: Kyoto University, Kyoto, Japan



*(B) Nonlinear time-series analysis and active inference*

Our group strives to understand theoretical principles of organisms'
perception and behavior in adapting to the environment and extend the
knowledge to create intelligent agents. A postdoc position is available for
this research area. We are looking for a postdoc interested in, e.g., Bayesian
time-series analysis and control on nonlinear dynamics, the free energy
principle, and active inference.



The contract is yearly-basis and renewable *until March 31, 2025*.

Workplace: Kyoto University, Kyoto, Japan



A successful applicant should have a Ph.D. in theoretical neuroscience,
machine learning, physics, applied mathematics, or engineering, but not
limited to these. The applicant should demonstrate research experiences
with a strong publication record. Programming skills in Python or
willingness to learn it, will be valued.



To apply, please send a CV, a statement of research interest (maximum two
pages), and contact information of two references to
hideaki.shimazaki at gmail.com. Please indicate which job you are interested
in (A or B, or both). Either English or Japanese is accepted. The starting
date is flexible, while earlier arrival is appreciated. Screening starts *from
September 16th*. The salary follows the university rule and depends on the
expertise of an appointed researcher.



Please feel free to send me any informal questions regarding this post.



Sincerely,



Hideaki Shimazaki, PhD



Email:             hideaki.shimazaki at gmail.com

Webpage:        http://www.neuralengine.org





Ref:

Aguilera, M., Moosavi, S. A., & Shimazaki, H. (2021). A unifying framework
for mean-field theories of asymmetric kinetic Ising systems. Nature
communications, 12, 1197
<https://www.nature.com/articles/s41467-021-20890-5>.



Donner C, Obermeyer K, Shimazaki H. Approximate inference for time-varying
interactions and macroscopic dynamics of neural populations. PLoS
Computational Biology (2017) 13(1): e1005309
<http://dx.doi.org/10.1371/journal.pcbi.1005309>



Shimazaki H, Amari S, Brown EN, and Gruen S, State-space analysis of
time-varying higher-order spike correlation for multiple neural spike train
data. PLOS Computational Biology (2012) 8(3): e1002385
<http://dx.doi.org/10.1371/journal.pcbi.1002385>
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