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, whose modular nature suggests limitless variability in their structure and chemistry. In a multidisciplinary research project involving the University of Manchester, Oak Ridge National Laboratory and IBM
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a student with a background in Mathematics, Computer Science, or a related STEM discipline who is passionate about computer graphics and gaming. A prior interest or experience in ML/AI rendering
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to apply: Online applications are made at http://www.bris.ac.uk/pg-howtoapply . Please select ICASE Trustworthy AI For Industrial Applications on the Programme Choice page. You will be prompted to enter
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countries and beyond. Training and Career Development As a PhD student, you will join the Faculty of Science Graduate School, which provides a comprehensive programme of professional skills training tailored
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(usually chemical engineering or chemistry, or equivalent industrial experience, but please get in touch if you think your qualification may be relevant). Enthusiasm for research, the ability to think and
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the coordination guarantees. Applicants should have, or expect to achieve, at least a 2.1 honours degree or a master’s (or international equivalent) in a relevant science or engineering related discipline. Candidate
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management, computer science, information management and beyond. Supervisors Primary supervisor: Professor Tom Jackson Secondary supervisor: Professor Ian Hodgkinson Entry requirements At least a 2:1 honours
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Aviation Research and Technology Centre (DARTeC), leading advancements in aircraft electrification, autonomous systems, and secure intelligent hardware. Through collaborations with the Aerospace Integration
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Engineering, Physics or Materials Science Excellent English written and spoken communication skills The following skills are also highly desirable: Ability to program in Matlab, Python or similar Strong
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Requirements We will only consider candidates with a good Bachelor’s degree (ideally, a first, minimum 2:1) and/or a master’s degree in computer science, data analytics, health economics, or computational