38 assistant-professor-computer-science-data-"Multiple" Postdoctoral scholarships in Germany
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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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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 2 days ago
intriguing for you. Your profile Successful candidates have strong skills in computational molecular (bio)physics, structural biology and scientific computing, as well as a keen interest in
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computer science, bioinformatics or related fields Solid understanding of machine and deep learning and relevant frameworks (e.g. Pytorch or Tensorflow, Keras, scikit-learn, OpenCV) Proficiency in Python, Linux and
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: ausschreibung10-25@mpinat.mpg.de Apply now Max Planck Institute for Multidisciplinary Sciences Department of Theoretical and Computational Biophysics Prof. Dr. Helmut Grubmüller Am Faßberg 11 37077 Göttingen
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with the document issued in the original language. Submit the application online. Please note: If you have any technical questions or problems your local information and advice centres could not help you with, please
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graduate assistant for 19 hours per week for 12 months at Leipzig University. Application Papers Further information on the programme and the application requirements can be found on our website
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motivated PhD students, interns, and PostDocs at the intersection of computer vision and machine learning. The positions are fully-funded with payments and benefits according to German public service
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: Excellent Master’s degree (or equivalent) in computer science, engineering, or related disciplines (typically mathematics, physics). For Postdoc applicants: Excellent track record in computer science
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, enrichment analyses - biological interpretation of data Your qualification - PhD/MSc degree in bioinformatics, computer science, mathematics, life sciences - background in Machine Learning and/or RNAseq
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Engineering, Computer Engineering, Computer Science, or a closely related field Strong background in robotics fundamentals: kinematics, dynamics, control, planning Proficiency in programming (C++, Python), and