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Computation and Data Driven Design of Materials for Onboard Ammonia Cracking This exciting opportunity is based within the Advanced Materials Research Group at the Faculty of Engineering which
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networking with colleagues and students; planning and organising research resources and workshops. Successful applicants will have or be near to completing a PhD in computer science, information engineering
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networking with colleagues and students; planning and organising research resources and workshops. Successful applicants will have or be near to completing a PhD in computer science, information engineering
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£20,780 per year, and includes a 3-month fusion engineering CDT training programme as part of the 2025 Cohort. This project is co-supervised by Dr Chris Hardie from UKAEA. The UoB Materials for eXtremes
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fees will be covered for up to three years. Eligibility Applicants must have an undergraduate or postgraduate qualification in computer science, machine learning, AI or another relevant field. Equivalent
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Computation and Data Driven Design of Materials for Onboard Ammonia Cracking This exciting opportunity is based within the Advanced Materials Research Group at the Faculty of Engineering which
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Physics, Theoretical physics, Maths or other closely related subject (e.g. Materials Science with evidence of strong computational background and skills). To apply, please contact the supervisors; Dr Thomas
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A PhD studentship in RF and Microwave Engineering is available within the Birmingham Emerging Device Technology (EDT) Research Lab, one of the leading interdisciplinary research groups within
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chemistry, physics, materials science, computer science or other related discipline. This 42-month studentship comes with a budget for training, conference attendance as well as for travel between Birmingham
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; EPSRC Centre for Doctoral Training in Green Industrial Futures | Bath, England | United Kingdom | 11 days ago
: Analyse how curation and drying impact mechanical properties and hygrothermal performance. Develop a Predictive Model: Create a computational model linking operational variables and material properties