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to join the Mead Group to contribute to a major research programme focused on characterisation of in vivo models of myeloid neoplasms and correlating findings with analysis of patient material. You will
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: PhD or equivalent degree in Robotics, Computer Science, Machine Learning, AI, Control Engineering, or a related field. Excellent programming skills and experience with related tools and software. A
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, Mechanical, Thermal Engineering or Computer Science. Experience Experience in conducting high quality academic research. Demonstrable ability to write material of a quality commensurate with publication in
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with an international reputation for excellence. The Department has a substantial research programme, with major funding from Medical Research Council (MRC), Wellcome Trust and National Institute
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of computational and behavioural neuroscience with modelling and domestic chicks’ data. This position is funded by a Leverhulme Trust project entitled “Generalisation from limited experience: how to solve
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at the School of Engineering & Materials Science, Queen Mary University of London. The appointee will collaborate closely with researchers in the Centre for Bioengineering, the Faculty of Medicine and Dentistry
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largest protein/peptide mimotope dataset foundational for advancing any peptide-based drug discovery programme. The ERC PoC PepVerse project focuses on increasing the technology readiness of this platform
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), and their research teams in the Quantum Light and Matter group. The overarching goal of the research is to synthesise and study artificial quantum materials using ultracold CsYb molecules arranged in
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of life and material sciences to adopt this facile technology. We forecast a potentially game-changing impact on a global scale that reaches further than the scientific benefits associated with this project
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but is not limited to systematising a database of materials, assessing their relevance, and also conducting systematic searches across legal databases and other sources to identify further materials