Master thesis: Information Under Fire: POMDP Models of Information in VR Threat Environments

Master thesis:
Information Under Fire: POMDP Models of Information Seeking in VR Threat Environments

Job Offer from February 04, 2026

Responsible co-supervisor:
Sara Ershadmanesh
Formal supervisor:
Peter Dayan
Supervising Collaborator:
Dominik Bach (Bonn)

The Department of Computational Neuroscience at the Max Planck Institute for Biological Cybernetics focuses on building and testing theories and computational models of neural processing, with a particular emphasis on decision-making, learning, and representation.

In dangerous or unpredictable environments, humans must decide whether to keep collecting rewards (e.g., food) or to seek information that helps them stay safe. In this project, you will analyse how people plan under threat and how they trade off explicit reward against information-seeking for safety. We have built a scenario in which biological agents forage for food and must stay clear of threats.

We have also collected data from humans performing this task in virtual reality. The goal of the project is to develop computational models based on Partially Observable Markov Decision Processes (POMDPs). These models characterize belief formation about a threat’s distance and speed, and how these beliefs guide planning in this situation. We will study both optimal behavior and heuristics computational strategies that may explain individual differences in this experiment.

What is available:

• Behavioral dataset from a VR experiment
• Collaboration with researchers at the University of Bonn (VR expertise and behavioral analyses)
• The active and rich environment at the Computational Neuroscience lab (supervised by Peter Dayan), where you are expected to participate in group activities as well as pursue your Master’s project.
• Improve and clean existing code
• Extend POMDP model to generate optimal behavior
• Compare model predictions to human behavior
• Write the Master thesis

Qualifications/

Experience:

• Strong programming skills are essential (Python or R)
• Knowledge of POMDPs and experience implementing related models (more experience is a plus)
• Short description of your experience with POMDPs and computational modeling
• Names and email addresses of two referees

The Max Planck Society is an equal opportunity employer:
Handicapped individuals are strongly encouraged to apply, and so are women in areas in which they are underrepresented. The Max Planck Society strives for gender and diversity equality. We welcome applications from all backgrounds and aim for a fair hiring process—so applicants should not include a photo in their application documents.