29 post-doc-image-processing Postdoctoral positions at University of London in United Kingdom
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: 23.59 hours BST on Sunday 08 June 2025 Interview Date: Friday 27 June 2025 Reference: CBS-0112-25 We are looking for a skilled and motivated Post Doctoral Research Associate to join the Structure and
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is the 1st of July, 2025. The position is a full-time post, limited to three years. We also offer a generous reward package and benefits including: Competitive and attractive pension package Generous
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hours BST on Tuesday 27 May 2025 Interview Date: Friday 06 June 2025 Reference: CBS-0080-25 We are seeking to appoint a skilled and motivated researcher to join our team. This post-doctoral research post
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on autofluorescence (AF) imaging and Raman spectroscopy for detection of metastatic lymph nodes during breast cancer surgery. Engaging with and reporting to Dr Alexey A. Koloydenko (Department of
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exploiting cutting-edge mechanobiological, as well as imaging approaches2-5 with the aim to investigate the role of mechanical sensing and memory in cardiovascular disease. The postholder of this British Heart
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techniques (including PCR) and cell imaging. Previous experience of organ-on-a-chip approaches or in vitro models and experience of working in musculoskeletal tissues is desirable but not essential. The post
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About the Role A 12 month post-doctoral research assistant position funded by the Barts and the London Charity (BTLC) is available in the laboratory of the laboratory of Professor Stuart McDonald
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: “Investigating the combined impact of behavioural and neurodevelopmental disorders on education.” The post holder will be an integral part of Dr Malanchini’s Cognition, Development and Education (CoDE) Lab
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About the role The Post-Doctoral Research Assistant will be a highly motivated individual keen on a Cell Biology research career. Using cutting-edge Super-resolution microscopy, the PDRA will
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responsibility for implementing a deep learning work-package as part of a Cancer Research UK-funded programme, developing an image-recognition model to identify morphological features corresponding to clonal