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-funded DECIPHER-M consortium (9 partners, €9M), we are building multimodal foundation models that integrate imaging, text, and structured clinical data to predict metastasis risk and identify tumor origin
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interaction scores. Build and deploy machine learning and statistical models for functional genomics predictions, including sgRNA efficiency and drug sensitivity scoring. Collaborate with laboratory members
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create predictions for how foragers should vary in their stay-or-leave decisions for different types of decision algorithm. You will then get to test those predictions using data from humans and rodents
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applications for a joint professorship under the Jülich Modell with the Hasso-Plattner-Institut für Digital Engineering gGmbH (HPI) to be filled as soon as possible: Full Professorship (W 3) for Software Testing
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the High Temperature Gas-cooled Reactor (HTGR) as the most credible Advanced Modular Reactor (AMR) technology. Achieving improved performance requires accurate, high-fidelity modelling to reliably predict power
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at developing and applying multiscale numerical models for the thermal-hydraulic safety analysis of advanced nuclear reactors, with a focus on the prediction of Critical Heat Flux (CHF) in Small Modular Reactors
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technology. Development of cutting edge foundation models for protein design, small molecule property prediction, or protein function prediction Data generation and curation, including molecular simulation and
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temperature with ribbon density as the main product quality attribute. Additionally, the computational modelling approach will be exploited as an aiding tool to predict the product quality and eventually
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to the weather prediction and climate projections. This is mainly due to our lack of understanding of cloud/snow ice microphysics and over-simplified representation in models. On a broader sense, although weather
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for the analysis of mobility data and to propose novel mobility prediction models. Undertake fundamental and applied research on privacy-preserving information sharing for urban micro-mobility systems. Lead and