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fundamental engineering science with advanced experimentation to develop methods that inform and validate next-generation tyre friction models. Key objectives include: Developing innovative experimental
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-class or 2:1 (or international equivalent) Master’s degree in Computer Science, Robotics, Mechatronics or Electronic/Electrical Engineering, or a related field. • Knowledge of machine learning/deep
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: • Experience with programming (Python, MATLAB), • background in aerospace, computer science, robotics, or electrical engineering graduates, • hands on skills in implementation of fusion
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-electromagnetics ), which will substantially favour collaboration opportunities within University of Birmingham and afield. To apply, please click on the 'Apply' button above (physics programme) or (engineering
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sustainability assessment framework and computational tool using Model-Based Systems Engineering (MBSE) and lifecycle modelling techniques. Apply and test the framework through case studies (e.g., ADR, ISRU, In
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(i.e. LCD TVs). Augmented (AR) and Virtual Reality (VR) technologies are the next logical step in display device technology; however, they require novel solutions in engineering and physics to overcome
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(computer vision technologies). The interdisciplinary nature of this PhD will require the integration of environmental science, engineering, and community science methodologies. Supervisors: Primary
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to train tomorrow’s leaders in earth and environmental science. For further details about the programme please see http://nercgw4plus.ac.uk/ For eligible successful applicants, the studentships comprises
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of Birmingham and afield. You can apply here: https://sits.bham.ac.uk/lpages/EPS019.htm (engineering programme) or https://sits.bham.ac.uk/lpages/EPS005.htm (physics programme) clearly stating the title
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Research Studentship in Neural Engineering 3.5-year D.Phil. studentship Project: Sleep classification for implanted neurostimulation systems Supervisors: Dr. Joram van Rheede, Prof. Timothy Denison