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exchangers (HX) for optimizing thermal storage in silos. The researcher will deploy conjugate heat transfer CFD models and conduct simulations to provide high-fidelity predictions of available power, charging
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, genomic selection modeling, bioinformatics, proficiency in R, Python and/or Linux command line • Experience with DNA/RNA extraction and library preparation • Experience working with large-scale datasets
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already been awarded a PhD degree. Selection process You should submit your CV through a dedicated site: https://cv.newton-6g.eu/ Additional comments Position: Data-driven models for CF networks
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digital twins be used to provide on-line predictions as to the future expected evolution of these critical properties as the basis for safe reinforcement learning (RL) for on-line optimal control”. In
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Charité–Universitätsmedizin Berlin (Dr. Rosanna Sammons); for further information, see https://www.sfb1315.de/ - development of network models of the CA3 region of the hippocampus - investigation
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polygenic risk scores, rare variant burden scores, and integrative prediction models. Evaluate model performance and clinical utility. Identify therapeutic targets and causal risk factors for cardiovascular
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and validation of a predictive pipeline for excipient–biologic interactions Integration of experimental SAXS data with AI-driven structural modeling to predict oligomerization behavior and excipient
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the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Controlling pollutant emissions is one
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biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run high-performance numerical experiments
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the Telemark Canal , focusing on digital twin-based preparedness modelling for cultural heritage infrastructure. The primary objective of the position is to complete a doctoral education leading to a PhD degree