45 machine-learning "https:" "https:" "https:" "UCL" "UCL" Postdoctoral positions in Finland
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related to staff position within a Research Infrastructure? No Offer Description ELLIS Institute Finland is a newly established world-class research hub in AI and machine learning – and we are growing! We
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fields. Your research can be theoretical, applied, or span both. Deadline February 9, 2026. Where to apply Website https://jobrxiv.org/job/ellis-institute-finland-27778-postdocs-in-machine-learn
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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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processing, machine learning, statistics or related fields. Demonstrated expertise in ML/AI, with prior experience of applications in the healthcare domain, particularly in cancer research considered a strong
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/or Korte), 3. Conformal deformations of metric measure spaces and/or general regularity and convergence for graph-based machine learning using stochastic game theory and theory of metric spaces (with
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the research environment: Faculty of Agriculture and Forestry, University of Helsinki https://www.helsinki.fi/en/faculty-agriculture-and-forestry Viikki Campus https://www.helsinki.fi/en/about-us
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Postdoctoral Researcher in ML for Dynamical Systems Representation, Prediction, and State-estimation
to develop machine learning-enabled approaches for predictive modelling and state estimation for fundamental applications within physical sciences. Your role The main research responsibilities involve building
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-effectively predicting the rate of massively multicomponent organic, or organic-enhanced, new-particle formation in the atmosphere. We will combine our molecular-level model development with machine learning
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organic, or organic-enhanced, new-particle formation in the atmosphere. We will combine our molecular-level model development with machine learning and artificial intelligence methods, targeted validation