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Field
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machine learning, data science, mathematics or a computational science), or a postgraduate qualification with a major statistical component. There is scope for the role to be undertaken in a hybrid manner
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About us The Research Department of Structural and Molecular Biology (SMB) is a world leading academic centre that promotes multi-disciplinary research at the interface of structural, computational and chemical biology, pioneering multi-disciplinary approaches aimed to bridge across the scales...
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expertise ranging from mathematical modelling to chemistry, molecular and cell biology, material sciences and engineering, and medical devices. The Research Fellow will be working in collaboration with
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@seas.harvard.edu . Applications will be reviewed on a rolling basis. Basic Qualifications A Ph.D. in Mathematics, Computer Science, or a related field, by the start of the appointment. Additional Qualifications
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with strong analytical and numerical skills, and backgrounds in physics, theoretical neuroscience, applied mathematics, computer science, engineering, or related fields. Experience in relevant research
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. in Mechanics, Geophysics, Applied Mathematics, or a related field Expertise in earthquake source physics, fracture mechanics, or dynamic rupture modelling Strong background in continuum mechanics and
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mathematics) or should be close to submitting their PhD thesis. They should also have experience in handling longitudinal data and conducting microsimulation or agent-based modelling. Good communication and
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mathematical/theoretical physics from the 1st of March 2026, or as soon as possible thereafter. The position is located at the Department of Science and Industry Systems and reports to the Head of Department
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-motivated researcher Good paper reading and writing skills Excellent publication record, including top-tier journals and conference papers in the related fields. Strong in Mathematics with good knowledge
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Fellow appointment with benefits. Term: Two years Qualifications: The ideal candidate would have the following skills and attributes: PhD in Statistics, Quantitative Ecology, Mathematical Biology