[DMANET] PhD positions in TCS and combinatorial optimization in Copenhagen

The Department of Computer Science (DIKU) at the University of Copenhagen invites applications for PhD positions in theoretical computer science and/or combinatorial optimization.

The PhD students will be part of a world-leading research environment (currently ranked 6th worldwide by CSrankings.org), with a strong presence at top-tier conferences like STOC, FOCS, and SODA, and also with publications in premier AI conferences like AAAI, IJCAI, and NeurIPS. We are home to the Basic Algorithms Research Copenhagen (BARC) centre (barc.ku.dk), joint with the IT University of Copenhagen, and have extensive collaborations with the Technical University of Denmark (DTU) and with Lund University on the Swedish side of the Oresund Bridge, as well as with our many visitors. We aim to attract top talent from around the world to an ambitious, creative, collaborative, and fun environment. Using the power of mathematics, we strive to create fundamental breakthroughs in algorithms and complexity theory. While the focus in on foundational research, we do have a track record of surprising algorithmic discoveries leading to major industrial applications.

These positions are available for period of 3-5 years, depending on the current education level of the applicant. All our PhD positions are fully funded, employed positions (including travel money) that come with an internationally competitive salary. The starting date is negotiable but should ideally be in September 2022.

The application deadline is January 9, 2022. Please see https://employment.ku.dk/phd/?show=155288 for the full announcement with more information and instructions for how to apply. Informal enquiries are welcome and can be made to Jakob Nordstrom (jn@di.ku.dk), Rasmus Pagh (pagh@di.ku.dk), Mikkel Abrahamsen (miab@di.ku.dk), or Mikkel Thorup (mthorup@di.ku.dk). Candidates interested in working with other faculty in the Algorithms and Complexity Section at DIKU are also strongly encouraged to apply.


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