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avionics triggered by the interaction of the energetic particles with the electronics. The project will adapt and extend existing numerical codes to simulate these phenomena. Experiments and modelling will
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position in the area of machine learning and computer simulations. The focus of the PhD project will lie on developing machine learning models for clustering, classification, regression and reinforcement
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file by email to hannes.linkspam prevention@uni-tuebingen.de . The pdf file should contain: a cover letter, your CV and relevant certificates. The deadline for applications is April 28, 2026. Equally
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spoken Strong motivation to work at the interface of microbiology and immunology. Send your application as one pdf file by email to hannes.linkspam prevention@uni-tuebingen.de . The pdf file should contain
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of Ecosystem Dynamics and Forest Management attn. Violeta Aramayo Hans-Carl-von-Carlowitz-Platz 2 85354 Freising Germany Email: bewerbung.edfm@ls.tum.de We ask you to send your application as a single pdf file
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learning and computer simulations. The focus of the PhD project will lie on developing machine learning models for clustering, classification, regression and reinforcement tasks to work with, enhance
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Max Planck Institute for Intelligent Systems, Tübingen, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | about 1 month ago
, biology and medicine. Using unique 3D & 4D capture facilities, machine learning, computer vision and advanced graphics, we are modeling every nuance of how humans and animals look and move. We develop
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workflow that maps first-principles electronic-structure data onto predictive atomistic spin-Hamiltonians and device-scale dynamical models. The candidate will run high-throughput, relativistic DFT
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. Submissions of applications proceed through an electronic form. Please visit this page to access the application form. During the application process you will be asked to select up to 3 people you plan
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Position (m/f/d). A full-time PhD position is available in a Max Planck research project within the WEAVE collaborative grant AtomDensityMap. Our project aims to extend the capabilities of electron