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addressing composite failure, damage mechanisms, and structural behaviors. Develop tools and models for virtual certification, integrating data-driven and physics-based approaches. Developing digital tools
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Faculty or Department: Faculty of Engineering and Applied Sciences Based at: Cranfield Campus, Cranfield, Bedfordshire Hours of work: 37 hours per week, normally worked Monday to Friday. Flexible
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frameworks, such as PyTorch (preferred) or TensorFlow, with a preference for experience implementing SOTA models and training procedures from academic journal papers. Development of data engineering pipelines
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Temporary/Per diem Organization Type: Higher Education Institution Required Education: Doctorate/Professional Internal Number: JR102485 Job Description Summary The Department of Engineering Technology at
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an emphasis on technology, data science and the humanities. The Nutrition, Metabolism and Health Programme is addressing one of the world’s most pressing healthcare issue: Over nutrition driven chronic diseases
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passionate plant science researchers, bioinformaticians or remote sensing/data scientists with skills in image processing or phenotyping with a collegiate and self-driven attitude towards multidisciplinary
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. Our dedicated and compassionate faculty and staff are driven by a common mission: Contribute to innovative approaches in predicting, preventing, and curing diseases, shaping the future of medicine
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, and real-time human health coaching. CADENCE D-PHA also aims to incorporate AI-driven assistance for cardiovascular disease patients through digital health coaching by leveraging large audio models and
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networks in order to enhance fog net technology. The planned work is experimental and will be conducted in our lab facilities, also incorporating theoretical models of complex flow. Fieldwork is planned in
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-driven models to optimize solvent systems. Mentoring the training and learning of PhD and undergraduate students on sustainable biomass conversion topics Assist in report/document/further grant writing