Postdoc on Decision Trees for Control and Monitoring of Stochastic Systems

Delft University of Technology (TU Delft); Nederland; On-site; EUR 45,000 - 65,000; Full time

Benefits offered by this job

ABP pension

Dual Career Programme

Education opportunities

Leave hours 232 per year

Health insurance discount

Job summary

TU Delft invites applications for a 1-year research position in the Algorithmics Group within the Department of Software Technology, EEMCS. The project focuses on decision-tree policies, explainable monitoring, and scalable synthesis for sequential decision making. You will work with PhD students and postdocs and may co-supervise under Prof.

Anna Lukina. You will join a vibrant international community at TU Delft, with opportunities to publish in leading venues and to contribute to open-source

Qualifications

• PhD in computer science or a related field (or close to completion).
• Strong foundations in mathematics and logic; experience in algorithm design and combinatorial optimization.
• Publication record in top venues (e.g., CAV, TACAS, RV, NeurIPS).
• Excellent written and spoken English.

Responsibilities

• Develop and advance learned controllers and decision-tree policies.
• Explore explainable monitoring and runtime verification approaches.
• Collaborate with PhD students and postdocs and co-supervise when appropriate.
• Aim to publish in leading venues and contribute open-source tools.

Skills

Excellent English

Formal methods

Planning under uncertainty

Machine learning

Sequential decision making

Education

PhD in computer science or related field

Job description

Delft University of Technology (TU Delft)

Organisation/Company Delft University of Technology (TU Delft) Research Field Computer science » Programming Computer science » Cybernetics Researcher Profile Recognised Researcher (R2) Application Deadline 23 Nov 2026 - 22:59 (UTC) Country Netherlands Type of Contract Temporary Job Status Not Applicable Hours Per Week 40.0 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

Our recent algorithms synthesize optimal tree policies orders of magnitude faster than earlier approaches. Now we want to take them into uncertain, real-world settings.

Job description Learned controllers are increasingly deployed in safety-critical settings, yet they offer few guarantees once reality deviates from the model they were trained on. Decision trees offer a promising alternative: they are compact, human-readable, and amenable to formal analysis.

This position builds on the recent results from our group. Possible directions include:

• Explainable monitoring: designing interpretable runtime monitors that identify which environment the system is operating in, so the right policy can be selected, or so that to detect when the deployed policy’s guarantees no longer hold.
• Scalability and stochasticity: extending search-based synthesis of decision-tree policies to stochastic and black-box systems and to larger state spaces, so that optimal tree policies remain within reach for realistic problems.

You will have the freedom to shape the direction within this scope. The aim is to publish in leading venues in formal methods and AI, along with open-source tools.

You will join the Algorithmics Group in the Department of Software Technology, Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS). You will collaborate with PhD students and postdocs working on intelligent decision-making and will have opportunities to co-supervise students. You will be supervised by Prof. Anna Lukina.

Job requirements You should have:

• a PhD in computer science or a related field (or be close to completing one), with a background in formal methods, planning under uncertainty, or machine learning for sequential decision making;
• solid foundations in mathematics and logic, plus experience with algorithm design, combinatorial optimization, and implementation;
• a strong publication record relative to career stage, for example, at venues such as CAV, TACAS, RV, AAAI, IJCAI, or NeurIPS;
• excellent written and spoken English.

The following are a plus:

• experience with (uncertain or robust) Markov decision processes, probabilistic model checking, or reinforcement learning;
• experience with decision trees, branch-and-bound search, mixed-integer programming, or runtime verification;

TU Delft (Delft University of Technology) Working at TU Delft means contributing to solutions that really make a difference.

For over 180 years, we have been training engineers who make an impact worldwide in companies, government bodies, or as entrepreneurs. Our alumni turn knowledge into concrete solutions for the challenges of today and tomorrow.

These challenges are changing rapidly. That is why we focus on themes such as energy, climate, digitalisation, artificial intelligence (AI), and smart mobility every day. Our education and research are directly aligned with what society needs now and in the future.

At TU Delft, our people make the difference. With their knowledge and curiosity, our staff provide a high-quality education and conduct pioneering research that extends beyond the campus. You will have the opportunity to take the initiative, work with others, and grow as a professional.

Working at TU Delft means join an international community of professionals and students. Together, we create knowledge, innovations, and solutions that help move the world forward.

Faculty of Electrical Engineering, Mathematics and Computer Science The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three scientific disciplines. Combined, they reinforce each other and are the driving force behind the technology we all use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation of equipment – which of course includes AI. Meanwhile we are pushing the limits of applied mathematics, for example mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. In other words: there is plenty of room at the faculty for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1000 employees and 4,000 students work and study in this innovative environment.

Click here to go to the website of the Faculty of Electrical Engineering, Mathematics and Computer Science.

Conditions of employment

• Duration of contract is 1 year. Temporary.
• A job of 36-40 hours per week.
• Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities.
• An excellent pension scheme via the ABP.
• The possibility to compile an individual employment package every year.
• Discount with health insurers on supplemental packages.
• Every year, 232 leave hours (at 38 hours). You can also sell or buy additional leave hours via the individual choice budget.
• Plenty of opportunities for education, training and courses.
• Partially paid parental leave
• Attention for working healthy and energetically with the vitality program.

Will you need to relocate to the Netherlands for this job? TU Delft is committed to make your move as smooth as possible! The HR unit, Coming to Delft Service , offers information on their website to help you prepare your relocation. In addition, Coming to Delft Service organises events to help you settle in the Netherlands, and expand your (social) network in Delft. A Dual Career Programme is available, to support your accompanying partner with their job search in the Netherlands. .

Additional information If you would like more information about this vacancy or the selection procedure, please contact Prof. Anna Lukina, via [e-mail] .