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machine learning. We focus on inductive logic programming (ILP), which learns logical rules from data. We primarily use automated reasoning techniques, such as SAT/ASP/SMT/MaxSAT solvers, to learn rules
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and machine learning. We focus on inductive logic programming (ILP), a form of inductive program synthesis which learns logical rules from data. The focus of this position is to develop ILP/program
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of the appointed researcher is - jointly with the research team - to design and conduct quantitative research, mostly on longitudinal register-based data on autoimmune diseases. Additionally, the researcher is
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. The project already includes existing datasets and established pipelines, and the successful candidates will contribute both by analyzing and extending these resources and by developing new data and approaches
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ecology predictions and empirical data on the evolution of sex-specific differences in immunity and life history traits. As we intend to conduct interviews also during the application period, we appreciate
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across connected forest–lake ecosystems. By integrating multi-taxa field data, trait-based ecology, experiments, and advanced statistical analyses, TRACE aims to uncover how ecological processes propagate
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knowledge, the goal is to elucidate bacterial genetic evolution that was shaped by human influence and make predictions to the future. The work provides the possibility to develop skills in microbiology, data
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academic transcripts 4. Contact details of at least two referees The deadline for applications is 22nd of March 2026, but the position will remain open until filled. For additional information, kindly