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—to macroscopic, population-level observables in rapidly evolving pathogens such as SARS-CoV-2 and influenza. Concretely, you will: formulate and analyze stochastic models of evolving populations using methods from
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and computer engineering, data science, informatics, biomedical engineering, or a related field. Job Description: A Postdoctoral Associate position in AI-driven drug discovery and/or computational
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experience and a strong interest in shaping the future of computation-driven design and multiphysical modelling. Subject Solid mechanics Subject description The position includes research and doctoral
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switching in corresponding devices. In this project, we first plan to make optimized engineering of metal stacking involving light elements promoting the required orbital polarization and demonstrate
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AI-driven learning technologies on learning outcomes, cognitive development, and mental health. Details: The ideal candidate will have methodological expertise in one of the following areas: multimodal
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, Industrial Engineering, or a closely related quantitative discipline. • Demonstrated research expertise and strong publication record in Generative AI, VLMs and/or VLA models, and their applications in
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data-driven urban development in Morocco and across Africa. The research will support the understanding and management of environmental challenges in urban areas, including land degradation, soil sealing
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Note - This is a one-year, fixed-term position. This position has been deemed critical by the School of Engineering Dean's Office and is exempt from the hiring freeze. Visa sponsorship is not available
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models and project standards. You will develop a coherent, structured approach to prioritisation and build a delivery capability that accelerates outcomes for Manchester’s researchers, improves consistency
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lung tumors. We utilize a multifaceted approach that encompasses preclinical studies in immunocompetent syngeneic and genetically engineered co-mutational models of KRAS-mutant NSCLC as well as PDX/CDXs