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plans should be adjusted accordingly. There will be opportunities to supervisor multiple PhD students as a member of supervisory team. Applicants are required to have a PhD*, or equivalent professional
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and maintenance of equipment. Assists in co-supervision of Final Year Projects (FYP) or capstone projects students together with the project PI Job Requirements PhD or Master degree in a related field
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contribute to the creation of knowledge by undertaking a specified range of activities within an established research programme and/or specific research project. We are looking for a Research Fellow to work in
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Partnership Training (APT): A programme of work to co-design and evaluate the effectiveness of training a person with aphasia and their communication partner to communicate better together” (NIHR Number: 208121
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for the provision of strategic leadership and vision. Developing and leading a team of academic/research staff and post-graduate researchers (PhDs) to deliver research outputs of outstanding quality. Obtaining
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. Computational modelling approaches are frequently used alongside experimental research programmes and much of our research crosses traditional boundaries, including the relationship of biodiversity to the health
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successful appointee will be centrally involved in the delivery of the ARIA-funded Forecasting Tipping Points programme , and will work collaboratively with Professor Doug Benn (University of St Andrews) and
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responsibilities will include: Develop Diagnostic Assays: Plan and execute laboratory and computation processes to create and optimise diagnostic tools for infectious diseases. Conduct Molecular Research: Utilise
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to the creation of knowledge by undertaking a specified range of activities within an established research programme and/or specific research project. We are looking for up to two Postdoctoral Researchers
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the role Overview of the role We are seeking a highly motivated Research Fellow in Machine Learning to join the PharosAI team, focusing on developing novel machine learning methods in computer vision