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well as partners from collaborating Universities and industry. At Surrey, we adopt an integrated approach that combines experimental studies, multi-physics and data-driven modelling, explainable AI, and techno
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, and AI-driven computational biology. The successful candidate will develop and apply innovative computational methods to analyse large-scale multi-omic datasets, identify mutational patterns across
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& optimization modelling, and data-driven assessment of compliance pathways, fuel transition, and strategic implications for shipping and maritime ecosystem. Key Responsibilities Conduct quantitative and scenario
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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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vivo models of bacterial infection to determine antibacterial efficacy and support progression of promising candidates. The project is highly collaborative and milestone-driven, providing an opportunity
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Bio Process Development Unit (ABPDU ). In this exciting role, you will develop AI-driven predictive metabolic models of cell physiology, metabolism, and functional behavior. You will have the
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sustainable infrastructure. In this role, the successful candidate will develop and validate advanced numerical models of energy micropiles, undertake large-scale simulations and data-driven analysis to explore
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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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technological progress in our increasingly digital, data- and algorithm-driven world. Integreat develops theories, methods, models, and algorithms that integrate general and domain-specific knowledge with data
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, multi-site provincial initiative that will advance our understanding of how genetic factors influence cardiac structure and function, and yield AI models that link phenotypic findings with genetic data