运筹offer:一周学界招聘总结（2023.7.17-2023.7.21）

This post is funded by DMS-EPSRC grant “The Power of Graph Structure”, that is led by Professor Kristina Vušković (University of Leeds) on the UK side and by Professor Maria Chudnovsky (Princeton University) on the USA side. You will join the thriving Algorithms and Complexity Research Group at the School of Computing at the University of Leeds and will collaborate with both PIs on the project research agenda.

This project focuses on developing techniques for structural and algorithmic study of hereditary graph classes, with the aim of gaining insight into the boundaries of what is computationaly feasible. We aim to understand how to exploit structure in order to construct efficient algorithms for classical optimization problems, such as colouring, clique and stable set problems.

Holding a PhD (or have submitted your thesis before taking up the role) in Mathematics, Computer Science or a closely allied discipline; you will have research experience in, but not limited to, structural graph theory, combinatorial optimization and graph algorithms.

£36,333 to £43,155 p.a.

Closing Date: Tuesday 25 July 2023

The Department of Computer Science at TU Dortmund University is offering the following positions (starting at the earliest opportunity):

Three professorships in the field of Machine Learning and Artificial Intelligence (Open Rank: W3 tenured or W2 with W3 tenure track)

The professorships are part of the Lamarr Institute for Machine

Learning and Artificial Intelligence.

Profile of the professorship

You represent the area of Machine Learning and Artificial Intelligence in research and further develop this at a top international level. The professorships are part of the Lamarr Institute and integrate research, teaching and transfer into the Institute's five core and five interdisciplinary research areas. Your potential research agenda includes: Foundations of Artificial Intelligence (AI), Theory of Deep Learning, Neuro-Symbolic AI, Explainable AI, Causality, Machine Learning (ML) and Logic, Fairness and Transparency of ML, Ressource Aware ML, Reinforcement Learning, Large-Scale Generative Models, Simulation-Based ML, Large Scale Optimization, Federated Learning or Future Applications of ML. Beyond this, you participate in research networks and cooperations in the Lamarr Institute as well as within and outside TU Dortmund University (e.g. Research Center Trustworthy Data Science and Security, Fraunhofer IML, Fraunhofer ISST, TU Dortmund Center for Data Science and Simulation (DoDaS)). You are committed to promoting early career researchers and

participate appropriately in the teaching activities of the Department

of Computer Science, especially concerning the areas of Machine

Learning and Artificial Intelligence. 

In the case of a W2 professorship with W3 tenure track, the successful candidate will initially be appointed as a temporary civil servant for five years. At the end of this five-year period at the latest, the tenure track will lead to continued employment as a tenured W3 university professor, provided that the necessary aptitude, competence and academic performance have been demonstrated and that the legal requirements pertaining to Section 38 of the North Rhine-Westphalia Higher Education Act (Gesetz über die Hochschulen des Landes Nordrhein-Westfalen, HG NRW) are met.

You obtained a doctorate with above-average success and acquired a post-doctoral lecture qualification (Habilitation) or an equivalent qualification. You demonstrated your research excellence in the field covered by the professorship through continuous international publications in recognized peer-reviewed venues. You also have experience in acquiring third-party funding. For the W3 professorships, continuous international publication achievements at a high level as well as a high international visibility of the scientific achievements, especially in the last five years, are expected. Applicants for the W3 professorships can already demonstrate success in the independent competitive acquisition of third-party funding, including cooperative joint projects. All applicants have the potential for teaching excellence. Social and leadership skills and the willingness to participate in academic self-administration complete your profile. Moreover, the recruitment requirements in Sections 36 and 37 HG NRW apply.