70 programming-"https:"-"FEMTO-ST"-"UCL" "https:" "https:" "https:" "https:" "https:" "Dr" positions at UNIVERSITY OF HELSINKI
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Project: Statistical modelling the Evolution of Sex-Specific Differences in Life History and Immunity Supervisors: Dr. Elina Numminen, Faculty of Science, University of Helsinki, and Dr. Piret Avila
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The Ecological Synthesis Group (ESG), led by University Researcher Dr. Caio Graco-Roza, invites applications for a Doctoral Researcher (PhD student) to join the research group at the Lammi
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POSTDOCTORAL RESEARCHER IN FUNCTIONAL COMMUNITY ECOLOGY / META-ECOSYSTEMS The Ecological Synthesis Group (ESG), led by University Researcher Dr. Caio Graco-Roza, invites applications for a
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We are recruiting a half-time Research Assistant for Dr. Jeremy Land’s University of Helsinki Rector-funded Project "QuILT: Quantifying Illicit and Licit Trade in the Early Modern Economy " at
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supervise theses particularly in the Bachelor’s Programme in Cultural Studies and the Master’s Programme in Cultural Heritage, as well as supervise doctoral theses and teach in the Doctoral Programme in
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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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leadership. The role requires a versatile language scholar who, in addition to specialist expertise in Russian, possesses skills aligned with the University’s strategic plan and the focus areas
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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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have solid skills in programming and working with libraries for training and using machine learning models. Previous experience in managing large volumes of data and high-performance computing is
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. Demonstrated experience in machine learning–based image analysis / computer vision, preferably using microscopy data Strong programming skills in Python Additional background in AI and machine learning