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program Arctic Ocean 2050. The successful applicant will work with zooplankton data from the High Arctic to address knowledge gaps in life history strategies, phenology and the distribution of key
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Dalton Building at Manchester Metropolitan University. You will develop skills in computational experimentation, financial data analytics, and systemic risk modelling, with extensive opportunities
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alters molecules and their properties, with focus on photoexcited states. The candidate will be member of the eT program developer team (www.etprogram.org) and developed models will be implemented
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, Computer Science and the Biosciences. You will be supervised by Amanda Wright (Optics and Photonics Research Group, Faculty of Engineering), Mike Somekh (Optics and Photonics Research Group, Faculty
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Materials, mastering scientific machine learning, uncertainty quantification, and high-performance computing. Your models will inform fusion design and advance AI-for-materials. Perfect for physics, maths
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Electronics, will use computational simulations to study how thin films form during flowable chemical vapor deposition (FCVD), a process used to build advanced semiconductor devices. Unlike traditional CVD
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explores how people of different ages play together, focusing on the experiences and perspectives of all participants. Working within a broader research program, the candidate will collaborate with
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-generation regenerative materials. This interdisciplinary project combines mechanical, materials, and biomedical engineering, offering training across fabrication, nanomechanical analysis, and computational
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the National Respiratory Audit Programme mandates that hospitals identify and address medication non-adherence, there are no evidence-based medication adherence interventions implemented in hospital respiratory
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Machine Learning for Image Classification. Eligibility You must: We would like you to have: sound knowledge of machine learning, computer vision and image processing strong programming skills. How to apply