Postdoc: Probabilistic ML for Sequential Decisions

DTU — Technical University of Denmark; Denmark; Remote; DKK 420,000 - 520,000; Full time

Job summary

DTU Compute in Denmark seeks a postdoctoral researcher to advance probabilistic machine learning and active inference for sequential decision-making under uncertainty. You will develop novel models, implement them with PyTorch, and evaluate on realistic use cases such as dynamic pricing.

The position includes publishing in leading journals, collaborating across disciplines, and contributing to teaching and supervision activities within DTU Compute.

Qualifications

• PhD in ML or related field.
• Strong ML/DL theory and practical skills.
• Proven publication record in journals/conferences.
• Experience with PyTorch and JaX or similar frameworks.

Responsibilities

• Conduct independent and collaborative research on probabilistic ML and active inference for sequential decision-making under uncertainty.
• Develop novel models/algorithms and implement/evaluate them using modern ML frameworks.
• Disseminate results through publications and participate in scientific collaborations.
• Contribute to the academic environment at DTU Compute, including limited teaching and supervision.

Skills

Probabilistic ML

Deep learning

Analytical/mathematical skills

Python & ML frameworks (PyTorch, JaX)

Publication record

Education

PhD in ML / signal processing / data science or related field

Tools

HPC/GPU environments

Job description

DTU Compute in Denmark seeks a postdoctoral researcher to advance probabilistic machine learning and active inference for sequential decision-making under uncertainty. You will develop novel models, implement them with PyTorch, and evaluate on realistic use cases such as dynamic pricing.

The position includes publishing in leading journals, collaborating across disciplines, and contributing to teaching and supervision activities within DTU Compute.