Postdoc position in ERC CoG project "CertiFOX" on trustworthy combinatorial optimization

il y a 3 semaines


Leuven, Belgique KU Leuven Temps plein

Candidates should hold (before start-date of the position) a PhD degree in computer science (or closely related)Candidates are expected to have experience with combinatorial optimization algorithms (e.g., SAT solving, constraint solving, MaxSAT, SAT modulo theories, Answer Set Programming, (Mixed) Integer Programming, ...). Proficiency in English is requiredThe field of combinatorial optimization is concerned with developing generic tools that take a declarative problem description and automatically compute an optimal solution to it. Often, users specify their problem in a high-level, human-understandable formal language. This specification is first translated into a low-level specification a solver understands and subsequently solved. Thanks to tremendous progress in solving technology, we can now solve a wide variety of NP-hard (or worse) problems in practice. Moreover, these tools are increasingly used in real-life applications, including high-value and life-affecting decisions. Therefore, it is of utmost importance that they be completely reliable. The central objective of this proposal is to develop methodologies and tools with which we can guarantee with 100% certainty that the right problem has been solved correctly.To achieve this ambitious objective, we will build on recent breakthroughs in proof logging, where solvers do not just output an answer, but also a machine-verifiable proof (or certificate) of correctness. However, a major limitation of current techniques is that correctness is not proven relative to the human-understandable specification written by the user, but relative to the low-level translation that the solver receives, meaning that there is no guarantee that the solver is solving the original problem. In this project, we will investigate end-to end guarantees of correctness. When successful, this will have a major impact on the way combinatorial optimization software is developed, evaluated, and used: the proofs produced will enable (1) debugging, since proofs contain detailed information about where bugs occurred, (2) auditability, since proofs can be stored and checked by an independent third party, and even (3) rigorous evaluation of algorithmic improvements. The successful candidate will perform research that advances the state-of-the-art in proof logging in general, and in particular focus on bringing proof logging to human-understandable language. More information on the research topic can be found on the project website [5]. The selected candidate is in this context expected to take up some mentoring responsibilities towards PhD students and MSc students working on the project. The Declarative Languages and Artificial Intelligence (DTAI) Section of the Department of Computer Science of the KU Leuven is one of the leading research groups for artificial intelligence, machine learning and data science. It is internationally renowned for its pioneering work on the integration of learning and reasoning, in domains such as statistical relational and neural-symbolic AI, probabilistic and inductive programming, logical and relational learning and their applications. In addition to fundamental research, the DTAI group applies the developed techniques to concrete cases situated in data science, sensors, sports analytics, combinatorial optimisation, robot manipulation and navigation, natural language processing, smart electronics, computer vision, etc. For these applications, DTAI often cooperates with other groups and companies from strategically chosen research areas.We are looking for an excellent researcher to strengthen Bart Bogaerts' research group on Knowledge Representation and Combinatorial Optimization. Bart Bogaerts' group will join the KU Leuven (by becoming part of DTAI lab) in October 2024. We are particularly looking for someone who can strengthen the recently-launched research line on proof logging (also known as certifying algorithms) for combinatorial optimization. In this line of research, the goal is to develop methods and algorithms that can guarantee with 100% certainty that the answers produced by a combinatorial optimizer are correct. Recent breakthroughs in this direction have resulted in a distinguished paper award at AAAI 2022as well as a series of tutorials at major conferences (CP, IJCAI). A (short) online version of this tutorial can be found online.We offer a fully-funded postdoc position, initially for 12 months, but renewable and with expected duration of two or three years. The position comes with a competitive salary (academic salaries in Belgium are very competitive) or an equivalent scholarship, as well as with travel budget. This is a pure research position, but it also comes with the possibility to participate in advanced teaching (while this is encouraged, it is not mandatory).



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