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image processing or phenotyping with a collegiate and self-driven attitude towards multidisciplinary research. About the Role The role includes carrying out fundamental plant science research related to a
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passionate plant science researchers, bioinformaticians or remote sensing/data scientists with skills in image processing or phenotyping with a collegiate and self-driven attitude towards multidisciplinary
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, neuroimaging, neurophysiology, proteomics, transcriptomics, epigenomics, metabolomics, bioinformatics, cell models and animal models. First in man and Phase 2, 3 and 4 clinical trials are also strongly supported
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lab investigates how neural circuits process visual information and drive behaviour, as well as the evolutionary development of these visual systems. By studying a myriad of vertebrate species, we aim
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. Experience of working with industry partners and collaborative working will be extremely valuable but is not essential. Similarly, prior experience with spatial biology, omics or bioinformatics would be
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the role Overview of the role We are seeking a highly motivated Research Fellow in Machine Learning to join the PharosAI team, focusing on developing novel machine learning methods in computer vision
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, neuroimaging, neurophysiology, proteomics, transcriptomics, epigenomics, metabolomics, bioinformatics, cell models and animal models. First in man and Phase 2, 3 and 4 clinical trials are also strongly supported
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the role Overview of the role We are seeking a highly motivated Research Fellow in Machine Learning to join the PharosAI team, focusing on developing novel machine learning methods in computer vision
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of siRNA-peptide conjugates across multiple human, primate and mouse cell lines. We are therefore seeking a highly motivated and organised individual with proven expertise in human tissue processing and cell
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, neuroimaging, neurophysiology, proteomics, transcriptomics, epigenomics, metabolomics, bioinformatics, cell models and animal models. First in man and Phase 2, 3 and 4 clinical trials are also strongly supported