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POST-DOCTORAL RESEARCH FELLOW - CEVIPOL (Centre de la vie politique) – Université Libre de Bruxelles
" Scientific knowledge and skills Candidates must have: Advanced training in quantitative methods (panel data, causal inference, multilevel modeling) Strong proficiency in R Experience with panel/time-series
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the pharmacoepidemiology work package (WP1), which is led by Professor Hedvig Nordeng at the PharmaSafe research group. The project integrates pharmacology, epidemiology and causal inference to examine how hormonal
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Postdoctoral Fellow in Neutrino Astrophysics Position in the School of Physics - Otte Research Group
simulations, neutrino physics, statistical inference, detector modeling, or large-scale computing frameworks is highly desirable. Applicants should submit the following: • Cover letter • Statement of research
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desirable. Familiarity with explainable AI, causal inference, or biologically inspired neural networks, as well as experience collaborating with experimental laboratories, will be considered strong assets
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calculating and representing pan-genome relationships, methods for inferring gene families, and methods for inferring evolutionary events from large collections of gene families. The participant will also have
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, methodology (including relevant discussions of causal inference), and research design as well as a time-line for completion of the research. The proposal must include a paragraph declaring if and how AI
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 2 months ago
inference and/or machine-learning approaches. You will be able to articulate and prosecute an innovative interdisciplinary research vision, contribute new modelling or analytical methods, and integrate
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evolution, historical biogeography, phylogenetic diversity, and speciation. Aims with this project are to use new methodologies to explore the evolution of taxa and characters and to infer centres of species
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and conducting original research and through publication as appropriate to the disciplinary area. To deliver research related to the project “AI enabled Satellite Morphological Inference from
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, using dynamic Bayesian networks to understand, propagate and reduce uncertainty in their assessments. The research will apply models of distributed situation awareness and ecological interface design