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: A completed university degree (Master or equivalent) in computer science, data science, applied mathematics, physics, materials science, or a related field Prior experience in computer vision, deep
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highly motivated doctoral student to join an ambitious project aimed at building machine and deep learning models to study the genetics of human disease. Funded as part of the Helmholtz AI program, the
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international network. This project is offered as part of a Hans Fischer Senior fellowship through the TUM Institute for Advanced Studies (https://www.ias.tum.de/ias/start/ ) and will be co-supervised by
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Berlin, and the Max Planck Institute in Hamburg. Our work combines physics, chemistry, and materials science – pushing the frontiers of quantum materials research. The overarching goal of the Collaborative
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builds bridges between past and future, between community and academia. Funded by the German Research Foundation (DFG), the RTG aims to reveal enmity as a processual, relational, and deeply ambivalent
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per semester in EUR None Combined Master's degree / PhD programme No Joint degree / double degree programme No Description/content The International Helmholtz Research School for Nanoelectronic Networks
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The Network Analysis and Modelling uses machine learning to investigate how genetic variation shapes gene regulation, protein function, and, ultimately, observable plant traits. We are seeking a
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digital technologies. At HPI, you benefit from close supervision by experienced professors and postdocs, cutting-edge research facilities, and a collaborative academic network, e.g. with the University
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semiconductor properties to the composition of lead-free double perovskites Your Profile: Master’s degree in theoretical or computational physics, chemistry, materials science, or a similar field Familiarity with
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, K. M. (2025). Quantum-Centric Alchemical Free Energy Calculations. 1–35. http://arxiv.org/abs/2506.20825 [3] mimic-project.com Your Profile: University degree (master’s) in physics, chemistry