32 programming-"https:"-"FEMTO-ST"-"UCL" "https:" "https:" "https:" "https:" "https:" "https:" scholarships at Technical University of Munich
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to design and evaluate programs that enhance community wellbeing. The project is a collaboration between the University of Global Health Equity (Rwanda), TUM, NYU Abu Dhabi, and the Government
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, or a related discipline Interested in climatology/meteorology as well as quantitative methods Prior experience in programming is a plus (e.g., using R or Python) Good communication skills and a high
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also on power systems in the CoSES lab at the Technical University of Munich. Previous Work https://mediatum.ub.tum.de/doc/1731060/g5zgxaj96lcyhh8gh6le1xbuu.Wetzlinger-2023-TAC.pdf https
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and networking opportunities within the Munich AI ecosystem and within structured graduate programs: the Munich Centre for Machine Learning (MCML), the Munich Data Science Institute (MDSI), the local
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programming and know how to use version control. ▪ You are experienced in the usage of machine learning (e.g., Actor-critic algorithms, deep neural networks, support vector machines, unsupervised learning
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) - Semantic 3D Scene Understanding - Face / Body Tracking, 3D Avatars - Non-Linear Optimization - Media Forensics / Fake News Detection How to Apply: Follow the instructions on our application platform: https
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(https://soilsystems.net/ ), a Priority Programme (SPP 2322) funded by the Deutsche Forschungsgemeinschaft (DFG; German Research Foundation). Within SoilSystems, scientists from different disciplines from
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discipline Strong interest in automation of process steps (Python, LabView, or similar... Experience in one (or more) of the following areas is desirable: programming, automation, synthesis of inorganic
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platform for early detection of cardio-metabolic diseases as well as characterization and classification of skin diseases. You will be part of our highly impactful research programs funded by European and
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production, agriculture broadly, and/or smart technologies is desirable. • Experience in modelling biological or agricultural systems, with strong programming skills (R, Python, or Matlab