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are seeking a PhD candidate to join our young team (Computational Systems Medicine) within the context of the BMFTR-funded DIASyM (https://diasym.mscoresys.de/ ) project, to develop new statistical and
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students will have the opportunity to work together with internationally recognized scientists and develop their research projects in an innovative research environment. We also have a PhD Association, which
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produce data that looks plausible but violates physics and is therefore of limited use for grid planning. As a PhD candidate you will develop physics-informed, domain-constrained generative models
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for sustainable transport planning. The purpose of this PhD project is to develop modelling approaches that improve the ability to analyse future desirable transport scenarios under deep uncertainty. A central
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Western Europe. Your duties and responsibilities include: Developing a concrete and feasible research project fitting the overarching theme and resulting in the defence of an article-based PhD thesis
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work demands and maintain critical thinking. The project combines empirical research with scale development and validation to better understand the conditions under which AI-supported collaboration
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connections between robots. The central hypothesis of this PhD is that these interaction terms can instead be represented by a generic Foundation Model capable of capturing local physical interactions across
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. As part of your PhD training, you will gain hands-on experience with advanced techniques, including CRISPR-Cas9 genome editing, protein and RNA biochemistry and biophysics methods. You’ll also develop
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practical guidance for leaders, boards, and governance bodies on responsible AI use, effective oversight, and leadership development in the age of AI. Your work Study leader-employee-AI triads and the ways
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career adaptability, supervisory and organisational support, opportunities to use and develop skills, and job satisfaction and engagement help explain why some employees come through AI-driven change with