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1,000 employees from over 50 nations, it is the largest institute of the Max Planck Society . The Research Group Computational Biomolecular Dynamics (Prof. Dr. Bert de Groot) is inviting
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Areas of study Neuroscience, Physics, Applied Computer Science, Bioinformatics, Computer Science, Engineering Informatics, Medical Informatics, Chemistry, Analytical Chemistry, Inorganic Chemistry
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extensive professional networking opportunities A structured PhD program with a comprehensive range of continuing education and networking opportunities - more information about the PhD program at the HZDR
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Performance Computing ( ZIH ) at TUD is available for computational modelling work. The Graduate Academy at TUD offers a comprehensive training program and individual career counseling for early career
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course program. Please visit our webpage https://www.cui-advanced.uni-hamburg.de/en/career/job-openings.html for more information on our available positions and the application process. Selection process
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theoretical and/or computational research in Nonequilibrium Statistical Physics and Active Matter, under the supervision of Ramin Golestanian. For more information concerning our current areas of research
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will engage in theoretical and/or computational research in Nonequilibrium Statistical Physics and Active Matter, under the supervision of Ramin Golestanian. For more information concerning our current
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of the scientific themes of the RTG Collaborating with other project partners of the RTG Active participation in the structured training program of the RTG including ring lectures, research and PhD seminars
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Description The Chair of Applied Mathematics at the Faculty of Mathematics and Geography at the KU Eichstätt-Ingolstadt invites applications for a position as Doctoral candidate in Applied Mathematics/ Approximation Theory to be filled by the earliest possible starting date. The Chair of Applied...
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: university degree (Master or diploma) in physics, biology, computer science, or a related field excellent background in RDM principles and FAIR data practices, ideally gained in a scientific environment