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the Intel-Merck consortium (the AWASES programme), available as soon as possible (at latest by September 2024). The postholder will work with Dr. Bora Karasulu (University of Warwick, Chemistry Department
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. This PhD project will take advantage of recent developments in machine learning methods, to enable computer modelling of the mechanical behaviour of titanium alloys to produce a machine learning-based
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data-driven elements. There is potential to explore a variety of specific applications of this work throughout the PhD project which lies at the intersection of interests of enthusiastic specialists with
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this PhD project you will build on the atomic cluster expansion (ACE) approach (e.g. using the ACEpotentials.jl or MACE codes) to tackle inverse problems. This approach is attractive for inverse problems as
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awarded £11m to train PhD cohorts in computation modelling. Built around a closely knit, highly collaborative team of academics from five science departments at Warwick with a strong track record in leading
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, superalloys, smart fluids, space plasmas etc. They have recently been awarded £11m to train PhD cohorts in computation modelling. HetSys is built around a closely knit, highly collaborative team of academics
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world’ systems across a range of research themes such as nanoscale devices, new catalysts, superalloys, smart fluids, space plasmas etc. They have recently been awarded £11m to train PhD cohorts in
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at the University of Warwick, benefiting from the stimulating and supportive environment and bespoke training programmes. The successful candidate will receive training to develop their knowledge and expertise in