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Job Description Are you interested in working at the intersection of optimal control, AI algorithms, and game theory, on problems that matter for real-world critical infrastructure? This PhD
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. To do so, you will combine atomistic simulations (density functional theory and ab-initio molecular dynamics simulations) with new machine learning models to parameterize machine learning force fields
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Denmark. The work consists of quantitative research, including developing research questions, conducting theory-driven statistical analyses of longitudinal register data, and, where relevant, linking
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chance to connect and work with leading researchers in the Copenhagen region and abroad. Responsibilities and qualifications The focus of the PhD project is on advancing the theory and practice of secure
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be learned from these firms for innovation practice and theory. The research departs from the premise of the Danish Innovation Index: firm innovativeness can (and should) be assessed by those who
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Are you passionate about chemical theory and computation? Are you interested in the real-time (atto- to picosecond) dynamic changes in molecules when they undergo physical and chemical
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Job Description Are you passionate about chemical theory and computation? Are you interested in the real-time (atto- to picosecond) dynamic changes in molecules when they undergo physical and
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-efficient, open-loop optimisation of fermentation control profiles, building on recent theoretical developments in optimal control theory, reinforcement learning and numerical methods as well as laboratory
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are just examples for inspiration and are not exhaustive for potential methodological approaches. Within the overall framing of the project, the PhD candidate will decide the research questions, theory, and
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complex materials simulations. These agents will assist with setting up, executing, and optimizing electronic structure workflows, from standard ground-state Density Functional Theory (DFT) calculations