Postdoc: Explainable Decision Trees for Stochastic Control

TU Delft; Delft; On-site; EUR 45,000 - 60,000; Full time

Benefits offered by this job

ABP pension

Annual leave 232 hours

Flexible employment package yearly

Relocation support

Job summary

TU Delft’s Algorithmics Group in the Department of Software Technology, Faculty of Electrical Engineering, Mathematics and Computer Science is seeking a Postdoc to advance decision trees for control and monitoring of stochastic systems. You will work with PhD students and other postdocs, shaping the research direction and contributing to high-impact publications and open-source tools.

You will join a dynamic team supervised by Prof.

Qualifications

• PhD in computer science or related field with focus on formal methods, planning under uncertainty, or ML for sequential decision making.
• Solid foundations in mathematics and logic; experience with algorithm design and combinatorial optimization.
• Excellent written and spoken English.

Responsibilities

• Develop decision-tree policies for control and monitoring of stochastic systems.
• Extend search-based synthesis to stochastic and black-box systems and larger state spaces.
• Publish results in leading venues and contribute to open-source tools.

Skills

Algorithm design

Combinatorial optimization

Uncertainty planning

Machine learning sequential

Formal methods

Publications

English proficiency

Education

PhD in computer science or related field

Job description

TU Delft’s Algorithmics Group in the Department of Software Technology, Faculty of Electrical Engineering, Mathematics and Computer Science is seeking a Postdoc to advance decision trees for control and monitoring of stochastic systems. You will work with PhD students and other postdocs, shaping the research direction and contributing to high-impact publications and open-source tools.

You will join a dynamic team supervised by Prof.