774 phd-in-computer-vision-and-machine-learning Fellowship positions in United Kingdom
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to 31 March 2027. The successful applicant will carry out experimental and computational work related to this project. The post will include the following duties: To undertake research, to act as research
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United Kingdom Application Deadline 21 Sep 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job
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: Genomics, precision medicine, bioengineering, and health data science AI and Digital: Machine learning, robotics, digital health, and cybersecurity Defence and Advanced Manufacturing: Secure systems
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researcher with a PhD in forest ecology or a related field, possessing strong field research skills, data analysis expertise, and the ability to work collaboratively in a multidisciplinary environment. You may
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and supervision of research students, primarily at the undergraduate level. You may be a great fit if: You are a dedicated researcher with a PhD in forest ecology or a related field, possessing strong
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in statistics, machine learning, mathematical modelling, or a related field, to join our research team in the Department of Applied Health Sciences. The successful candidate will work on an NIHR funded
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field relevant to the interface of energy technology, economics, data science and public policy. Examples of relevant disciplines include (but are not limited to): any physical, mathematical, computer or
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Programming and Software Development AI/Machine Learning (AI/ML): Research and Publication Additional information For informal queries, please contact: Professor Dimitra Simeonidou: Dimitra.Simeonidou
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with a strong background in computational modelling or scientific machine learning. You will also have the ability to conduct independent research and a developing track record of publications in
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will a have a relevant PhD and medical degree alongside registration with the GMC at Specialist Registrar Garde or below. You will have a recent track record in histopathology and use of machine learning