COMPUTATIONAL NEUROSCIENCEPhDApplications Closed

Shervin Safavi

Dresden, Germany

Position Details
Apply by May 31, 2025
PhD
Dresden, Germany

Application deadline

May 31, 2025

Job

Job location

Geocoding

Dresden, Germany

Quick Information

Application Deadline

May 31, 2025

Start Date

Flexible

Education Required

See description

Experience Level

Job

Job location

Geocoding

Dresden, Germany

Map

Job Description

The project will focus on developing reinforcement learning (RL) models to understand internal cognitive processes (in particular perception, and perceptual multistability; for example, see, Safavi and Dayan, Neuron 2022 and BioRxiv 2024). In the course of the project, we, together, will develop decision-theoretic models, for instance, based on partially observable Markov decision processes (POMDP), and assess them with psychophysical experiments, and will have the possibility to analyze neural data recorded from animals while doing similar tasks to understand the neural implementation of these computations.

https://docs.google.com/document/d/1qyuPbNznU9u0tLOuja_SuA0W3bTrz63LXlcwJ9mEi_4/edit?tab=t.0

Interested applicant can also send their application to DIGS-ILS (an structured PhD program in Dresden) - but deadline is slightly earlier May 6th.

https://www.digs-ils.phd/join/phd-positions

If you consider applying for DIGS-ILS, please also send your application via the portal noted above

Requirements

  • Broad familiarity with cognitive computational models (e.g.
  • reinforcement learning
  • Bayesian inference
  • recurrent neural networks) and psychophysics are advantageous.
  • (N) Have background (Master/Diploma) in computational neuroscience
  • neuroscience
  • physics
  • mathematics
  • statistics
  • machine learning
  • psychology
  • and other related fields.
  • Our wishes (N=necessary
  • D=desired
  • P=plus):
  • (N) Being comfortable with programming (best would be
  • Python
  • or/and Matlab).
  • (N) Communication skills in English.
  • (N) Willingness to work responsibly and within part of a team.
  • (D) Have experience with computational and cognitive neuroscience.
  • (P) Have experience in the analysis and modeling of behavioral data.
  • (P) Have experience with psychophysics experiments
  • (P) Have experience with training recurrent neural networks
  • (P) Have experience in the analysis of neural data.

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