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the tools of computational biophysics. Our research group is highly interdisciplinary, using everything from quantum chemistry, conventional and enhanced sampling molecular dynamics simulations, generative AI
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Description of the workplace The Division of Secure and Networked Systems at the Department of Electrical and Information Technology conducts broad research in cryptography, computer security
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for the development of the Ambient Pressure X-ray Photoelectron Spectroscopy Program at MAX IV. The beamlines provide a wide range of sample environments for in situ and operando XPS and XAS across four instruments and
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Description of the workplace The position will be placed at the division of Computer Vision and Machine Learning at the Centre for Mathematical Sciences. The Centre for Mathematical Sciences is an
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also be included in the duties. This position is primarily a research position that combines experimental and computational work. You will, in particular, be responsible to develop and implement a novel
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that the applicant has a PhD, or an international degree deemed equivalent to a PhD, within the subject of the position. The certificate proving the qualification requirement is met, must be received before
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that the applicant has a PhD, or an international degree deemed equivalent to a PhD, within the subject of the position. The certificate proving the qualification requirement is met, must be received before
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, computer science, medical physics or other field relevant for the project. The PhD degree must be completed no later than at time the employment decision is made. The ability to develop and perform high-quality
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molecular structures capable of transferring electrons and interacting with light. Such assemblies also have applications in biomedicine. The primary objective is to develop computational methods, using deep
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strategies. The research group focuses on exploration of tumor immune microenvironments through spatial omics and imaging, development of computational models for prediction of molecular and clinical features