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position will contribute to the research programme of the recently founded "AI Hub in Generative Models", a research consortium funded by EPSRC. The goal of the programme is to do research in the area of
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treatment, material and energy flow analysis, integrated data modelling, systems dynamics modelling, circular economy, sustainability assessment performance, decision-support tool design Month when Interviews
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mathematical foundation of machine learning models. You will be responsible for developing scientific machine learning methodologies enabling new approaches for solving machine learning problems including
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focus on solid dosage forms and 3D printed drug products. The research will integrate advanced imaging, computational modelling, and pharmaceutical sciences to improve the resolution, reproducibility, and
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methods for defect detection; Apply AI and machine learning techniques to process, analyze, and interpret complex NDE data; Create AI models for automated defect detection, classification, and
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Genetics, Reproduction and Development (GRAD) Large Research Group to: Use single-cell omics techniques to analyze human pluripotent stem cells, human embryos, and stem cell-derived embryo models. Study how
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research and real-world impact, leveraging one of the highest-quality financial datasets in the industry. What You’ll Do Conduct research and develop ML models to enhance trading strategies, with a focus on
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research and teaching as one of the world's top 80 universities. Embedded in an ecosystem of health, academia and industry, it delivers the research outcomes, skilled workforce, technology and partnerships
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the immune response to mpox in both animal models and in vitro systems. We are looking for a motivated PhD student to help advance this line of research. As a PhD student, you will: Design and conduct
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-22 eV or better, and powerfully test the Standard Model of particle physics. They further constrain CP-violating new physics at scales of 10-100 TeV, far beyond the reach of the LHC. The TUM and the