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. withdrawals, change of programme, leave of absence). Assisting with other activities associated with the change of status process, e.g. reporting to the Student Loans Company, sending standard confirmation
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will work with the programme leader, academics and practice partners to support students and will attend meetings across the partnership locations. They will be expected to contribute towards development
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Overview Data Connect, a service within the University's Research and Innovation IT team, is seeking an enthusiastic Data Scientist to contribute to the development and delivery of multiple health data assets. Data Connect works closely with stakeholders across our region including the South...
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Overview As a Project Engineer at the Advanced Manufacturing Research Centre (AMRC), you will have the opportunity to apply your skills to solve real-world manufacturing problems. Working within a multidisciplinary team at the Integrated Manufacturing Group (IMG) to develop novel solutions for...
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AMRC marketing teams Programme Administration & Support Be the point of contact for students and supervisors, and provide guidance and support on matters related to the PhD and EngD programmes Support
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scheduled team meetings. Liaise between individual students /groups of students and programme directors. Undertake module evaluation, including facilitating student feedback, reflecting on own teaching design
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scheduled team meetings. Liaise between individual students /groups of students and programme directors. Undertake module evaluation, including facilitating student feedback, reflecting on own teaching design
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a mixture of experimental and computation work. A current key focus of the group is development of new multiscale modelling approaches, coupled with data driven modelling techniques, to support
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these methods for thin coated membranes. As part of a team, you will develop mathematical and computational models, as well as lead the experimental work. You will work closely with our industrial partner. You
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Early-stage failure prediction in fusion materials using machine learning