[Comp-neuro] Postdoctoral researcher positions available, Laboratory for Integrated Theoretical Neuroscience at RIKEN Brain Science Institute, Japan

hnx hnx at brain.riken.jp
Mon Oct 28 06:37:00 CET 2013

Dear colleagues,

Applications are invited for opening positions for postdoctoral scientists to work at the Laboratory for Integrated Theoretical Neuroscience (Lab Head: Hiro Nakahara), RIKEN Brain Science Institute. Our laboratory’s long-term research goal is to understand the computational principles that underlie the way neural systems realize adaptive decision-making and associated learning. We work on two main areas, decision making and neural coding, using computational approaches and conducting human fMRI experiments. In this way, we build computational and mathematical models and analyze behavioral, neurophysiological, and imaging data, often closely combined with experimental investigations. (Find details about our laboratory on our website:  http://www.itn.brain.riken.jp). We are seeking enthusiastic and well-qualified postdoctoral fellows to join our research activities in any of the following topics. (This job advert is on http://www.brain.riken.go.jp/en/careers/20131021_h_!

1) Human fMRI experiments: We study value-based (reward-based) decision-making and learning as well as social decision-making and learning. We welcome candidates who want to investigate the underlying neural and cognitive processes with respect to key computations such as model-based analysis (e.g., reinforcement learning and Bayesian frameworks). We are also interested in the techniques of neural decoding and connectivity analysis, combined with model-based analyses, and extending our research into the domain of computational psychiatry. 

2) Modeling studies: We build computational and mathematical models for understanding the neural, cognitive, and computational processes of value-based and social decision-making. We are interested, for example, in integrating reinforcement learning with state representational learning and in investigating the relationship of model-free and model-based reinforcement learning in neural circuits. Circuit-wise, we are interested in the basal ganglia-related circuit, including dopamine neuron functions and in relation to prefrontal areas and other subcortical areas (e.g., the lateral habenula, amygdala, and neuromodulator circuits). 

3) Neural coding studies: We analyze neural data, particularly fMRI and neurophysiological data, often developing new methods of analysis. We address to the underlying neural mechanisms for decision-making and, more generally, contribute to understanding neural coding: computation and coding realized by the collective activity and interactions of neurons. With respect to fMRI data, we plan to advance model-based analysis, for instance, in combination with developing methods for neural decoding and connectivity analysis. As for neurophysiological data (e.g., via collaboration with experimental laboratories using animal experiments), we are analyzing dopamine neural activity from behaving monkey experiments, based on new theories of reinforcement learning, and are also planning to analyze large-scale simultaneous recording of neural activities from behaving rat experiments, with the aim of answering how neural interactions give rise to reinforcement and representational learni!

Applicants should have, or be expecting to receive, a Ph.D., and have research interest and background in the area of (or related to) research described above. Please send your application to itninfo at brain.riken.jp; for what to be sent as the application materials, please refer to http://www.brain.riken.go.jp/en/careers/20131021_h_nakahara_r.html. Application review will begin immediately and continue until the position is filled. Start date is flexible, but an early starting time is preferred. Informal inquiry should also be sent to itninfo at brain.riken.jp.

Best wishes,


Hiroyuki Nakahara, Ph.D.
Laboratory for Integrated Theoretical Neuroscience
RIKEN Brain Science Institute

hiroyuki nakahara 

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