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criteria BSc or MSc in molecular and cell biology, neuroscience, or a relevant subject area. Proven research aptitude and laboratory experience Ability to work independently and collaboratively Ability
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: Prof Ilias Tachtsidis (UCL Medical Physics and Biomedical Engineering) Secondary Supervisor: Professor Antonia Hamilton (UCL Institute of Cognitive Neuroscience) and Dr Flaminia Ronca (UCL Sport and
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techniques, including: Molecular biology, Tissue culture, Flow cytometry (FACS), qPCR, handling BSL2 pathogens - Experience analyzing next-generation sequencing (NGS) data, including exome and RNA sequencing
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demonstrate a commitment to multi- and/or inter-disciplinary research in the social sciences. Applicants are encouraged to propose creative approaches to cybersecurity communication, drawing upon the theory and
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Science & Public Policy. Together, we support an inclusive culture and diversity for our staff and students. We are committed to encourage further growth from a diversity of groups, and we look forward
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Sciences, Queen Mary University of London (QMUL). Candidates will complete a PhD and have an employment contract from QMUL. This project is funded by Marie Sklodowska Curie Doctoral Networks Actions
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requirements The candidate should have a distinction or merit MSc (or equivalent, or higher) degree in Data Science, AI, or a closely related subject. They should demonstrate aptitude for original research
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deep learning techniques to reconstruct full-duration PET data from shorter scans, ensuring clinical usability by maintaining diagnostic accuracy while improving patient safety and workflow efficiency
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: 3.5 years Funding Full coverage of tuition fees and an annual maintenance tax-free stipend of £21,237 for both home and overseas students. Information on fee status can be found at https
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engineering, food engineering, mechanical engineering, or related discipline. Good team working, observational and communication skills are essential with the ability to work independently and as a member of a