1,748 data-"https:"-"https:"-"https:"-"https:"-"https:"-"KU-LEUVEN" Fellowship positions
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for the Expansion of Wellbeing Archaeology (KNEWA). KNEWA will run for 1 year, it will collect and compare data on policies and delivery of WA in England, Denmark and Italy to advance understanding of what works in
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discipline (statistics, mathematics, computational biology, data science). Strong programming skills (R preferred) Statistical competence (Bayesian is advantageous) Please email the PI at ephdbsl
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and energy materials. Preference will be given to those with knowledge of computer programming, AI and/or machining learning. Applicants are invited to contact Prof. Jianguo Lin at telephone number 2766
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count data, offering a rare opportunity for applied research and experimentation. The postdoctoral research fellow will be supervised by the principal investigator Dr. Adrian Chong from the Department
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. • Experience with data analysis using statistical inference techniques. • Experience with health economic evaluations. • Experience with parallel and/or high-performance computing. • Familiarity with agent-based
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(DoE) plan Plan and execute experiments Capture and analyse data Resolve technical problems Perform technical research and technical report writing Requirements: PhD in Mechanical, Electrical and
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statistical data and an interest in the ways in which education can teach democratic values. The postholder will be part of a small research team based at UCL and the University of Roehampton and will play a
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months. Further information is available in the role profile. To apply for this vacancy please click ‘Apply Now’ to complete your details and upload a copy of your CV. Please contact Prof Ricky Wildman
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catalytic systems. The postholder will develop and apply advanced simulation techniques, analyse molecular simulation data, and contribute to collaborative research combining computational modelling with
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information about us, please visit: www.dbb.su.se . Project description The candidate will develop machine learning (ML) strategies, primarily revolving around interpretable ML and generative AI, to study