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, learning, visual literacy, collaboration, shared spaces, physical installations, user experiments. All details here: https://bivwac.fr/jobs/ Where to apply E-mail phd-26_bivwac@inria.fr Requirements Research
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hemocompatible coating strategies to improve membrane–blood interactions. - Model and optimize membrane performance using computational tools, machine learning, and artificial intelligence Work Plan - Synthesis
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motivated candidate with a strong background in statistics and/or machine learning. Areas of particular interest include, but are not limited to: Causal Discovery and Causal Inference Extreme Value Theory
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. The successful applicant will develop a predictive pipeline using atomistic modeling and machine learning to identify optimal "seeds" for directing crystal growth, followed by rigorous experimental testing
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certificate recommendation letters, if available (max 3) writing samples (max 3), e.g. PhD thesis and published papers Your Profile strong background in machine learning/artificial intelligence experience in
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Description Your Responsibilities We are looking for a highly motivated PhD student in the areas of Probabilistic Machine Learning and Neuro-Symbolic AI to contribute to the Cluster of Excellence “Bilateral AI
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this goal, doped-diamond systems will be considered. The thermal stability of selected compounds under operating conditions will be assessed by means of molecular dynamics simulations with Machine Learning
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Jönköping University and School of Engineering invites applications for a Lecturer in Computer Science with a focus on data science and machine learning. This position offers opportunities
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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
, leveraging on data analytics and machine learning to improve learning outcomes and engagement in the classroom, and Development of personal GPT-powered AI tutors that use the knowledge from (1) to provide
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molecular docking, molecular dynamics and free-energy methods (MD/FEP), machine learning for molecular design, and protein–ligand modelling. Experience bridging computational and experimental groups, and the