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industry. The center offers an excellent working environment with access to state-of-the-art technologies and an outstanding high-performance computing infrastructure. For TUD diversity is an essential
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positions in the areas of biochemistry, structural biology, biophysics, cell biology, systems biology, and computational biology. We are looking for outstanding graduates from all over the world to join our
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into goal-directed behavior. We use state-of-the-art approaches including functional brain imaging, automated behavioral analysis, and computational neuroanatomy. We value a collaborative atmosphere, early
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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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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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To Apply: To apply for the position, please provide the following materials as a single PDF file via email to Dr. Andreas Fischer (andreas.fischer(at)uni-greifswald.de): A letter of motivation detailing your
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that demand interdisciplinary solutions? Then the Program for Collaborative Doctoral Projects is the perfect opportunity for you. Many of today’s most pressing problems can only be tackled through
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that demand interdisciplinary solutions? Then the Program for Collaborative Doctoral Projects offers a perfect opportunity for you. Today’s most pressing problems can only be solved in cross-institutional
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that demand interdisciplinary solutions? Then the Program for Collaborative Doctoral Projects is the perfect opportunity for you. Many of today’s most pressing problems can only be tackled through
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and performing laboratory (wind-wave facility) experiments, using state-of-the-art imaging techniques developing computational codes to process and understand large experimental datasets (e. g., image