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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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of Helsinki. The main research fields at the department are artificial intelligence, big data frameworks, bioinformatics, data analysis, data science, discrete and machine learning algorithms, distributed
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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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the candidate's background and interests, ensuring a collaborative and engaging research experience. We seek candidates who have completed a PhD in ecological statistics or environmental economics or a related
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in vivo genetic mouse models, advanced live and intravital imaging, engineered microchip models, primary cell co-culture systems and novel microscopy and analysis methods. The research will provide