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Python, Julia or C++ Knowledge of modern deep learning frameworks (e.g. pyTorch) Knowledge of collaborative software development tools (e.g. Version control: Git) Experience working in Linux shell/cluster
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machine learning approaches. These are similar to earlier work on charge and excitation energy transfer (see https://constructor.university/comp_phys). The project for the PhD fellowship is slightly more
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for Molecular Genetics or Freie Universität Berlin, this doctoral program is your ideal pathway! The International Max Planck Research School for Biology and Computation is a collaboration between Freie
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of Prof. Dr. Frank Cichos and Dr. Nico Scherf (Max Planck Institute for Human Cognition and Brain Sciences). The position is part of a collaborative project in the Center for Scalable Data Analytics and
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. Correlating experimental, ab initio and multi-scale simulation as well as machine learning techniques is central to our mission: Development and application of advanced simulation techniques to explore and
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Description TUD Dresden University of Technology, as a University of Excellence, is one of the leading and most dynamic research institutions in the country. TUD has established the Collaborative
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learning, image analysis, and advanced computing to study relationships between structure and function. Keywords: Human Brain, 3D Atlas, Deep Learning, Temporal Lobe, Brain Function Entry Requirements
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of potentially novel modes of protein binding is possible in collaboration with other members of the lab. Desired (but not absolutely required) skills: programming in python, machine learning, and experience in
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performing data analysis of B cell receptor repertoire data using programming languages (mostly R) Successful candidates can think independently, are eager to acquire necessary new skills, and are excellent
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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