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equivalent) in Civil Engineering, Environmental Engineering, Hydrogeology, Geosciences, Environmental Sciences, or related STEM disciplines (e.g., Applied Mathematics, Physics, Computational Sciences
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. We are looking for highly motivated candidates with a strong academic background in computer science, AI/ML, bioinformatics, or related fields such as mathematics and statistics. Informal enquiries
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physical wellbeing. We are committed to progressing the diversity and inclusion agenda, for example; gender diversity in Science, Technology, Engineering and Mathematics (STEM) through our Athena SWAN Bronze
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, Mathematical Sciences, Materials Science and Engineering, and Chemical Engineering are welcome to apply. If you are seeking an exciting opportunity to become part of a multidisciplinary team of esteemed
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Application deadline: All year round Research theme: Applied Mathematics, Mechanical and Aerospace Engineering, Fluid Dynamics How to apply:uom.link/pgr-apply-2425 How many positions: 1 This 3.5
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level (or international equivalent) in a science, mathematics or engineering discipline. Applicants without a master's qualification may be considered on an exceptional basis, provided they hold a first
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, mathematics, engineering, computer science, or related subject) Proficiency in English (both oral and written). Knowledge in cryptography is desirable. Studentship and eligibility The studentship covers: Full
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
relevant field such as engineering, computer science, or applied mathematics. Experience or interest in AI, machine learning, or digital systems is beneficial. We welcome candidates from diverse backgrounds
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(physics, mathematics, engineering, computer science, or related subject) Proficiency in English (both oral and written). Knowledge in cryptography is desirable. Studentship and eligibility The studentship
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Supervised by: Rasa Remenyte-Prescott (Faculty of Engineering, Resilience Engineering Research Group) Aim: Develop a mathematical model for obsolescence modelling for railway signalling and telecoms