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to heiDOCS, the integral quality program supporting doctoral candidates and early postdocs at Heidelberg University How to apply: Please submit in a combined PDF document: (1) Motivation letter (2) Curriculum
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-learning models that connect powder characteristics and process parameters with the properties of the final components. These models will support faster feedstock qualification and enable predictive quality
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Explore opportunities for collaboration with researchers in SPH and across the University to expand and lead research initiatives to support the Collaborative Mentor postdocs and students within
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to the development of state-of-the-art nuclear-reaction models and evaluated nuclear-data libraries, supporting safe, reliable, and competitive technologies for both existing and future nuclear-energy systems, as
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are developing a suite of models to deliver a through-process microstructural and mechanical property prediction framework for steel. By integrating these models into a cohesive digital twin architecture, the work
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white matter. The network aims to strengthen the full translational pathway, from understanding disease mechanisms and developing disease models to preclinical therapy testing, clinical readiness and
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Are you interested in developing mathematically grounded methods for uncertainty quantification in deep learning, particularly for large language models in healthcare applications? Are you looking
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to staff position within a Research Infrastructure? No Offer Description The project explores extreme light–matter interactions at the nanoscale, developing advanced theoretical models in direct
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(further funding will be applied for) and focuses on power systems engineering in the context of the next phase of Iceland’s energy transition. It builds directly on established modeling work at Reykjavík
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unique opportunity to work at the interface of evolutionary biology, genomics, and algal model systems, while contributing to a broader understanding of biodiversity, adaptation, and genome evolution. Your