53 software-engineering-model-driven-engineering-phd-position Postdoctoral positions at Technical University of Munich
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06.12.2021, Wissenschaftliches Personal The professorship of Data Science in Earth Observation is seeking six new PhD candidates/PostDocs for its new center for Machine Learning in Earth Observation
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Technology (CIT) and TUM School of Medicine and Health is offering a 2y-4y postdoctoral full-time position in medical machine learning. The Computational Pathology Lab (https://schuefflerlab.org
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22.04.2022, Wissenschaftliches Personal The Professorship for Environmental Sensing and Modeling at the Faculty of Electrical Engineering and Information Technology is researching topics
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energy efficiency while keeping the grid reliable and secure. Our research method is engineering-oriented, prototype-driven, and highly interdisciplinary. Our typical research process includes
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for students. Requirements We require for the position the following: A Ph.D. in the field of Applied Mathematics, Computer Science, Computational Science and Engineering, or similar. Knowledge of numerics as
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focus on deep networks for solving inverse problems, learning robust models from few and noisy samples, and DNA data storage. The position is in the area of machine learning, with a focus on deep learning
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management. Our group combines empirical work (with experiments in the field and in the lab) and modelling techniques. The focus of this postdoctoral position is the generation of empirical datasets
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(with experiments in the field and in the lab) and modelling techniques. The focus of this postdoctoral position is the generation of empirical datasets for livestock systems in East Africa, and in
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the following areas: PhD in mechanical/electrical engineering, robotics, computer science, or a comparable field, Experience in self-reliant managing of research projects (financial and administrative) and
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on the nanoscale (previous works e.g.: https://www.nature.com/articles/s41563-019-0555-5). You will also supervise one PhD student who will work on a complementary topic guaranteeing quick output and an ideal