24 computational-physics-"https:"-"https:"-"https:"-"https:"-"FCiências" research jobs at Aarhus University
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We are seeking applicants for a 2 year-postdoctoral position to join us in the Optomechanics group at the Department of Physics and Astronomy in order to work with nanoguitar optomechanical
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graph algorithms for optimization under physical constraints Applying graph mining and graph data management techniques Designing computational methods for waste heat reuse and green transition goals
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This is a full-time (37 hours/week) on-site role located at Åbogade 34, 8200 Aarhus N, Denmark for a Postdoctoral Fellow at the Department of Computer Science, Aarhus University. The postdoctoral
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Join us at the Department of Electrical and Computer Engineering at Aarhus University for a postdoctoral position focused on deep learning based analysis of remote sensing data for groundwater
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We are seeking applicants for a 2-year postdoc in Ultrafast X-ray probes of Quantum Materials to join us at the Department of Physics and Astronomy. Starting Date and Period The position is for 2
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experience using and developing measurements and models to develop process-based understanding of greenhouse gas emissions like methane at field scales, and linking these to key environmental drivers
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is given the opportunity to comment on the part of the assessment that concerns him/her self. Once the recruitment process is completed a final letter of rejection is sent to the deselected applicants
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, neuroscience and personalised medicine. The Department of Biomedicine provides research-based teaching of the highest quality and is responsible for a large part of the medical degree programme. Academic staff
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description You will be contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will
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(including gastruloids) to study epigenetic regulation in development. An interdisciplinary environment with opportunities for collaboration across experimental and computational life sciences within MBG and