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engineering. We aim to unravel the logic of genome organisation and metabolic control—with the bold vision of building synthetic life. In this role, you will develop and apply computational methods to analyse
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programme. The particular emphasis of the project will be to examine the interaction between atherosclerotic plaque macrophages and neutrophil extracellular traps and how it impacts cellular function and
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. Department: Res Dept of Biomedical Computing. Contact details:Dr. Rachel Sparks. rachel.sparks@kcl.ac.uk Location: St Thomas Hospital. Category: Research. About Us We are seeking experts in medical image
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between the Hong Kong Polytechnic University (HKPU) and the Royal College of Art (RCA), funded by the Hong Kong SAR Government’s InnoHK programme. Drawing on the research excellence of both institutions
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experience in: Deep learning Medical imaging computing (preferably neuroimaging) Computationally efficient deep learning Deep learning model generalisation techniques. Translating deep learning models
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driven Postdoctoral Researcher to join the groundbreaking AI-Design Lab (AiDLab) – a major collaboration between the RCA and The Hong Kong Polytechnic University (HKPU), funded by the InnoHK programme
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are seeking to appoint a postdoctoral research associate as part of a UKRI Future Leader Fellowship funded research programme. The successful candidate will work as part of a team to develop and apply deep
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are seeking to appoint a postdoctoral research associate as part of a UKRI Future Leader Fellowship funded research programme. The successful candidate will work as part of a team to develop and apply deep
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the objectives and development of the research programme on the Oncogenic and Immunogenic Roles of Transposable Elements in Cancer. The appointed PDRA will be integrated into a multidisciplinary team and will
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of genome organisation and metabolic control—with the bold vision of building synthetic life. In this role, you will develop and apply computational methods to analyse single-cell modalities, focusing on gene