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simulations, density functional theory (DFT), molecular simulations, or machine-learning potentials. Experience with generative AI, active learning, uncertainty quantification, Bayesian optimization
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Railway Mechanics is the core of the competence center CHARMEC whose research focuses on the mechanical interaction between components in trains and tracks. Among other things, the research provides
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theory, network science, resilience theory, disruption modelling, mobility systems, urban analytics, computational social science, agent-based modelling, causal inference, or spatial data science
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documents: degree certificate or a statement of the expected date of defense, and two references with email addresses. We will happily handle your application via our ATS (Applicant Tracking System) ReachMee
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A well-documented track record of research interests and achievements in an area strongly related to the project You are expected to be somewhat accustomed to teaching, and to demonstrate good
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on the candidate’s profile and selected research track. About the research project DRIVE PR – Data-Driven Product Realisation is a large collaborative research initiative at Chalmers University of Technology and the
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no later than the time the employment decision is made Strong written and verbal communication skills in English A well-documented track record of research interests and achievements in a field relevant to
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industry, we advance sustainable, reliable engineering systems in an inclusive and supportive environment. Our research group, the Robot Athletic Intelligence Lab (RAIL), focuses on legged robotics and
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. Experience applying machine learning to networking problems, for example, reinforcement learning, graph neural networks, or uncertainty quantification. A track record of publications in leading networking
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. Experience applying machine learning to networking problems, for example, reinforcement learning, graph neural networks, or uncertainty quantification. A track record of publications in leading networking