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Do you have a computational background and interest in developing novel tools for integrating structural biology data to understand regulation of disordered regions of proteins? Then the Viennet lab
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DTU Physics seeks a talented and motivated postdoctoral researcher for a 2-year position in computational nanophotonics. The goal is to use inverse design, such as topology optimization
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to achieve the project goals. Candidates meeting the criteria for both positions are encouraged to apply for both positions separately. Project description Many adults suffer from hearing and vision (‘dual
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criteria for both positions are encouraged to apply for both positions separately. Project description Many adults suffer from hearing and vision (‘dual-sensory’) loss. Because these losses are typically
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Post Doctoral Researcher in Human-Centered AI for Software Engineering, Department of Electrical ...
The Section for Software Engineering and Computing Systems, at the Department of Electrical and Computer Engineering (ECE), invites applicants for a two-year postdoctoral position within the area of
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characterization. At SurfCat, we make extensive use of surface science techniques and collaborate closely VISION, which provides access to advanced microscopy tools. Promising catalysts may also be studied at large
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at CSIC and UCM in Madrid, as well as Aarhus University, in a joint effort between the ERC Synergy project METRIQS and the Villum Young Investigator programme DynamiQ. Responsibilities and qualifications In
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computational models to map co-expression networks and predict systemic disease transitions. Characterise intestinal microbiome changes and their correlation with inflammatory diseases. Computational modelling
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techniques and data analysis to provide a more integrated picture of life processes in the context of health and disease. To be a postdoc fellow at the AMBER programme you will get unprecedented medical
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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 be working primarily with