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of immunoglobulin production shape the survival of normal and malignant plasma cells. Using in vitro plasma cell differentiation systems, mouse models (9), and advanced molecular and cellular technologies (10), we
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of the existing strengths in the department, which include numerical weather prediction, climate modeling, high-impact weather and climate events, boundary layer meteorology, and surface hydrology
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perturbations. The numerical predictions will be systematically compared with available experimental data from IRPHE to assess accuracy and refine the model, ultimately leading to a validated numerical tool
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evaluating and piloting new technologies to improve team workflows and research quality. Experience implementing or using AI, predictive modeling, or advanced analytics to inform prospect identification and
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to work effectively in an interdisciplinary team. PREFERRED QUALIFICATIONS Experience with one or more of the following: knowledge graphs, graph machine learning, link prediction, representation learning
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funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The main objective of the project is to develop an instrument model to predict
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on the vision of developing multi-level thrombosis risk prediction models, from cellular dynamics to organ-level hemodynamics. The network integratesin silico, in vitro, and in vivo approaches to understand
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to predict thermal runaway on the cell level. The combustion and gas model developed on the cell level will then feed into the work to accurately predict thermal runaway on pack, module, and system levels
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are seeking two motivated researchers or engineers with expertise in finite element programming to join an ambitious project modelling the complete neuromuscular dynamics of Drosophila larvae. This position
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). Experience with Oracle EPM Cloud (EPBCS, PCMCS, FCCS, Strategic Modeling) and with ERP/GL, HR/Payroll, and student system integrations. Experience implementing rolling forecasts, predictive analytics