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physiology or neural strategies following pathology, which limits their clinical applicability. This PhD project focuses on the development and validation of an innovative neuro-musculoskeletal model
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experienced AI Engineer to contribute to the development and implementation of Large Language Model (LLM)-based agents within multi-agent systems for B2B decision optimization. This project aims to explore how
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predictive simulations, real-time control, and process optimization. You will work on the development of deterministic population balance models, conduct single-crystal and batch crystallization experiments
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an opportunity to engage in advanced modelling and optimization techniques with a focus on developing practical solutions for the mining industry. RESPONSIBILITIES: The tasks of this position include but are not
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and sea-ice model in collaboration with project partners. Refine and optimize the coupled ACCESS-OM3-ISSM model for improved computational performance and numerical reliability. Collaborate
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, extract statistical models, and compare findings across environments, hardware, and frequency bands. Collaborate with PhD students, postdocs, and faculty on joint projects, ensuring experimental results
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of optimal plasma parameters (exposure time, power, gas composition) before their application to more complex cellular models. In a second stage, the PhD student will develop models of chronic infected wounds
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. Candidates are also expected to teach post graduate student courses including but not limited to Convex Optimization, Probability Theory, Generalized Linear Model and extra. Job Requirement Candidates should
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job funded through 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 This PhD topic is funded
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are expanding our mission to harness the power of artificial intelligence for life sciences research, innovation, and impact. We are now looking for an Large Language Model (LLM) engineer to join the Machine