Dear colleagues,
at the Faculty of Mathematics at TU Dortmund, a position as a research associate (TV‑L E13) is to be filled in the near future (there is some flexibility with the starting date) within a research project funded by the Federal Ministry of Research, Technology and Space and led by Professor Paul Manns. The goal of the research project is to combine reinforcement learning with global optimization algorithms (branch‑price‑and‑cut) for mission planning of heterogeneous fleets of autonomous surveillance and inspection robots. The project duration is two years.
https://service.tu-dortmund.de/documents/18/2120797/w21-26_Job_advertisement_eng.pdf/d5a27bb5-599b-69a4-0282-73f5aac97472
Main responsibilities are
* Analysis, development, and implementation of a branch‑price‑and‑cut algorithm
* Analysis, development, and implementation of a reinforcement learning method
for the intended application.
* Evaluation of the algorithms using the simulation environment and real‑world data provided by the project partner
* Publication and presentation of results in international journals and at conferences
Ideal candidate profile:
* Solid knowledge of discrete optimization, ideally with a connection to vehicle routing problems, typically demonstrated through a relevant PhD in mathematics, computer science, or economics (operations research)
* Strong programming skills in Python and/or C++
* Experience with modern AI methods such as reinforcement learning is an advantage
* Excellent written and spoken communication skills in English
Complete applications including a CV, a publication list, and a list of potential people who are prepared to provide a letter of recommandation using the Reference number w21-26 should be sent until 31 May 2026 to: Technische Universität Dortmund, Sozialforschungsstelle, Ellen Hilf, Evinger Platz 17, 44339 Dortmund
Further information is available on request via email to paul.manns@tu-dortmund.de.
Please feel free to forward this information to potential candidates.
Thank you and best regards,
Paul Manns