15 parallel-computing-numerical-methods-"Prof" Fellowship positions at University of Leeds
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Do you have a background crossing the disciplines of computational mechanics and biomedical engineering? Do you have an interest in developing computational models to investigate the lubrication
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at the University of Leeds led by Prof Amanda Maycock to work on the NERC funded Pushing the Frontiers project entitled The Wide-ranging Impacts of STratospheric smoke Aerosols (TWISTA). Smoke aerosol generated by
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statistical methods. We are committed to supporting and developing our team members, through attendance at conferences and access to training in research methods, and will support you to further develop your
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Are you interested in astrophysics, and how advanced computational methods can be used to investigate the evolution of magnetic fields in neutron stars? Would you like to feel part of a strong
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to completion) in geophysics, physics, applied mathematics or similar highly numerical discipline with a strong background in computational modelling or scientific machine learning. You will also have the ability
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, shopping discounts and travel schemes are also available. And much more! To explore the post further or for any queries you may have, please contact: Prof Phil Wheat Email: P.E.Wheat@its.leeds.ac.uk View All
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Research Fellow in Patient Reported Outcomes (HALO: Haematology Lived Experience and Outcomes study)
contact: Prof Richard Feltbower, Professor of Paediatric Epidemiology Email: r.g.feltbower@leeds.ac.uk Dr Kate Absolom, Associate Professor of Applied Health Research Email: k.l.absolom@leeds.ac.uk Further
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. These findings will inform a new generation of Finite Element computational models that seek to include the complex behaviour of rocks into volcano deformation models. You will join and work with Dr Craig Magee
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the upper troposphere significantly impact Earth's radiation balance by trapping long-wave radiation. Three proposed methods aim to reduce global climate forcing by manipulating upper tropospheric/lower
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, cross-cutting Methodological Research, Education and Innovation (M-REI) Division, conducting statistical, trial conduct and mixed methods research inspired by real problems encountered in complex trials