92 machine-learning-"https:" "https:" "https:" "https:" "U.S" PhD positions at DAAD in Germany
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. Only online applications will be accepted. AVAILABLE PROJECTS: Nanoscience: Application of bistable DNA devices Biophysics: Learning in living adaptive networks Biophysics: High-resolution structural
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by colloids, as well as methods for immobilizing these ions. Modern methods of theoretical chemistry (first principles, kinetic Monte Carlo, machine learning) will be applied to investigate diffusion
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. Only online applications will be accepted. AVAILABLE PROJECTS: Nanoscience: Application of bistable DNA devices Biophysics: Learning in living adaptive networks Biophysics: High-resolution structural
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, the details of the process are not yet fully understood. Mechanistic learning, the combination of mathematical mechanistic modelling and machine learning, enables a data-driven investigation of the processes
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effects, this project builds on those results to model far-field behavior relevant for communication networks. The objective is to develop reduced-order surrogate models using physics-informed machine
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of Photogrammetry and Remote Sensing and together with other chairs being part of the RTG. Requirements: good or very good university degree in electrical engineering, computer science, computer engineering or
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individually, e.g., through training and networking opportunities specifically for doctoral candidates (JuDocS): https://go.fzj.de/JuDocs FAIR REMUNERATION: Depending on your qualifications and assigned
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graduates with expertise in the RTG-addressed PhD subjects, high interdisciplinary desire to learn and willingness to cooperate, very good verbal and written English communication skills as
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at gsnas.fu-berlin.de Required Documents Required Documents Motivation letter CV Certificates Research expose References Language certificate Application Application https://www.jfki.fu-berlin.de/en
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academic environment. Required Documents Required Documents CV Certificates Transcripts Language certificate Motivation letter References Application Application https://www.frankfurt-school.de/en/home/study