53 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at Technical University of Denmark in Denmark
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level? At DTU Physics we are looking for a postdoc to develop experimental exercises for the Engineering Physics B.Sc. programme, and to measure their effect on the learning. Responsibilities and
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predictive framework linking genomic data to extinction risk, working at the interface of evolutionary genomics, simulation modelling, and machine learning. By integrating forward-in-time simulations, real
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, modelling and machine learning to improve defect detection, classification and power loss simulations. Benchmarking field-acquired images with laboratory measurements. Publishing results in leading journals
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-efficient magnetic heating/cooling device. Qualified applicants must have: PhD degree in physics, astronomy, engineering, computer science or similar. Experience with finite element modeling, ideally Comsol
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, experimental and computational methods to study the physiology of microbes. You will work in a team contributing to projects of other team members, while independently developing your own project. You will also
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conferences. Contributing to the supervision of PhD students and the coordination with collaborating researchers. We are seeking a researcher with strong experience in experimental quantum optics and a clear
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Job Description Are you passionate about computational modelling and elastomeric materials? We are looking for a Postdoc to develop and apply state-of-the-art models for elastomeric materials and
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results at conferences, Teach and supervise BSc and MSc student projects, and be co-supervisor for PhD students You must have a PhD in macro-energy system modelling or a similar field. Strong coding skills
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experience in developing software for processing SURE and ULM data Have a desire to advance the field and help PhD students learn We offer DTU is a leading technical university globally recognized
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, you will contribute to research-based teaching and the supervision of student projects. Skills in mathematical modelling and machine learning of relevant physical glacier processes (ice sheet and