Postdoctoral Researcher in Applied Combinatorial Optimization in Zürich

We are looking for an outstanding candidate with a PhD in Mathematical Optimization or a related field, and strong interests in real-world mathematical optimization challenges, knowledge transfer, student supervision, and coding/software aspects related to modern applied combinatorial optimization techniques.

Your main responsibility of you is to take a pivotal role in research collaborations with industrial partners. This includes the design of algorithms for challenging real-world problems, the efficient implementation of such algorithms, and also being the main contact person for some of our industrial research partners. The position provides excellent opportunities to build a strong profile on the interface of academic and industrial research. It strengthens and expands the applied profile of the group, which complements a strong existing theoretical research thrust, and comes with exciting opportunities to contribute and shape existing applied projects and also spawn new ones, typically in collaboration with industrial partners. The Combinatorial Optimization Group is part of the Institute for Operations Research within the Mathematics Department of ETH Zurich. We are a well-connected research group with strong international visibility. We offer a very stimulating work environment with a highly competitive salary and benefits, excellent working conditions and infrastructure in the centre of Zurich, and generous travel support. The position is initially for two years with the possibility of an extension. The starting date is flexible within 2023.

• PhD in Combinatorial Optimization or a related field and strong interests in both applied Mathematical Optimization and mentoring
• strong coding skills
• excellent knowledge of mathematical programming techniques (including linear/integer optimization, mixed-integer optimization, local search techniques, and preferably also convex/nonlinear optimization)
• a solid theoretical foundation in Mathematical Optimization
• excellent academic qualifications
• very strong communication and organizational skills
• broad interest in the full spectrum of applied projects, from algorithm design to programming-related aspects
• Interest in learning and expanding programming-related skills for the design of highly performant and maintainable code, and the effective use of modern hardware through relevant techniques, like concurrency and GPU computations