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project is to develop a series of surrogate models focusing notably on Physics-Informed Neural Networks to emulate the process of sediment deposition, diagenesis, and potentially fracturing, working closely
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About the Role You will develop and apply novel computational methods to quantify the societal impact of fundamental science discoveries. Candidates close to completion of their PhD will initially
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ambitious who has obtained their PhD, has a strong portfolio of design practice and has begun an academic career in health research. The post holder will provide guidance to junior members of the research
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involves high level of collaboration with both the QMUL Space Plasma Group and the QMUL Detector Development Group. About You The successful candidate will have a PhD (or equivalent experience) in the field
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develop, synthesise and characterise materials for this project. About You The post is suited to a PhD graduate with a background in materials chemistry or a related discipline. If you have a vivid
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, Optical Communication Engineering, or related field. Candidates at the PDRA level must have a PhD Degree in Computer Science, Optical Communication Engineering, or related topics. Applicants should have
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collaborate with bioinformaticians, experimentalists and clinicians. About You Essential requirements for this post include a PhD in a relevant biological or computational subject and background in
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computational methods (Efremova et al. Nature Protocols, 2020; Jain et al., Genome Biology). About You PhD in a biological or computational subject and background in working with genomics data. About the School
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, or trans status or history. More information on our structures and initiatives around EDI, including information on staff diversity networks, can be found on our Equality and Diversity Intranet page .
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, or trans status or history. More information on our structures and initiatives around EDI, including information on staff diversity networks, can be found on our Equality and Diversity Intranet page .