Postdoc in Quantized RL & Discrete World Models

Syddansk Universitet; Odense; On-site; DKK 420,000 - 540,000; Full time

Job summary

Syddansk Universitet invites applications for a two-year postdoctoral fellowship in quantized reinforcement learning at the ADIN Lab, SDU, Odense. The project targets how continuous sensory input is distilled into discrete tokens to guide control in complex environments.

The successful candidate will develop uncertainty-aware world models, provide theoretical guarantees, and benchmark across state-of-the-art simulation suites, collaborating toward high-impact publications in top venues.

Qualifications

• PhD required in a relevant field (CS/Math/Stats/Theoretical Physics).
• At least two first-author papers at flagship ML venues (NeurIPS/ICML/ICLR/AISTATS).
• Strong background in statistical learning theory and RL foundations.
• Excellent command of English, both written and spoken.

Responsibilities

• Advance research on quantized reinforcement learning and embodied discretization.
• Develop scalable prototypes and benchmarks in high-dimensional simulations.
• Bridge theory with practical algorithms; publish in top ML venues.
• Fulfill standard teaching assistant duties as part of the residency.

Skills

Python

Reinforcement Learning

PyTorch/JAX

Mathematical Maturity

English Communication

Education

PhD in Computer Science/Mathematics/Statistics/Theoretical Physics

Tools

Git

DL Frameworks

Job description

Syddansk Universitet invites applications for a two-year postdoctoral fellowship in quantized reinforcement learning at the ADIN Lab, SDU, Odense. The project targets how continuous sensory input is distilled into discrete tokens to guide control in complex environments.

The successful candidate will develop uncertainty-aware world models, provide theoretical guarantees, and benchmark across state-of-the-art simulation suites, collaborating toward high-impact publications in top venues.