51 computational-physics-superconductor Postdoctoral positions at Nature Careers in Germany
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mathematics, computer science, physics, biomedical or electrical engineering or similar disciplines. Good programming expertise (Matlab, C++, Python or equivalent) and experience with the Linux operating system
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Area of research: Scientific / postdoctoral posts Job description: Researcher - Engineering & Physics for Biomedical Innovations (f/m/x) 102788 Full time 39 hrs./week Neuherberg near Munich
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Experimental Nuclear Physics (all genders) Posting ID: 25.64-1270 within the HISPEC/DESPEC collaboration, being one of the largest collaborations of the NUSTAR (Nuclear Structure, Astrophysics and Reactions
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skills in computational molecular (bio)physics, structural biology and scientific computing, as well as a keen interest in interdisciplinary research and collaboration with experimental groups. PhD
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. The Department of Mathematics and Computer Science, Hessain.AI research group “Artificial Intelligence – Deep Decision Support Systems”, led by Prof. Dr. Martin Becker, is currently accepting applications for a
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physical sciences, engineering, advanced microscopy techniques, and DNA nanotechnology. Biochemists, synthetic biologists, bioengineers, chemical biologists, chemists, or candidates with a computational
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PhD or equivalent qualification in computer science, statistics, mathematics, physics, and/or engineering, or a degree in biological science with demonstrated experience in computational and statistical
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completed PhD in (bio)informatics or (neuro)immunology A completed Master’s degree in biology, biomedicine, bioinformatics, or data science Basic knowledge in cell culture, immunology, and molecular biology
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. Please indicate in your application which of the above listed projects is most intriguing for you. Your profile Eligible candidates have strong skills in computational molecular (bio)physics, statistical
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Ph.D. or equivalent degree in mathematics, physics, computer science, bioinformatics, or a related field Experience in developing deep learning models Ideally, prior experience in analyzing biological