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PhD studentship: Discovery of rational therapeutic biomarkers in breast cancer by systems pathology and deep learning Supervisor: Dr Hamid Raza Ali Department/location:Cancer Research UK Cambridge
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interface of machine learning, deep learning, data science and applications in forest sciences. Together with the Director, you will further develop KIForst as a faculty-wide platform for methodological
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dysbiosis drives immune dysregulation and disease progression in pediatric patients, generating new clinical multi-omics data and using deep learning, structural equation models, and causal inference
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language processing that address concrete problems and are both theoretically rigorous and interpretable. The PhD is funded by the ERC CoG PANDORA (Deep Multimodal Learning for Mining and Generation of Arguments
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learning and physics, addressing key challenges in modern quantitative biology. The successful candidate will be responsible for: • Develop and train deep learning models (CNNs, ...) data to predict IPLSs
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methods tailored to ILC. The PhD researcher will fine-tune and benchmark pathology foundation models using multi-site H&E and immunohistochemistry whole-slide images. The aim is to learn representations
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. Kindly submit your CV and motivation letter to the attention of Mr. Menno Koeslag, HR Advisor. Where to apply Website https://www.academictransfer.com/en/jobs/364035/phd-candidate/apply/ Requirements
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qualifications include: Strong research experience in deep learning and foundation models, including experience with pre-trained models, fine-tuning, transfer learning, or self-supervised learning. Experience with
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of Researchers (Charter and Code ). Please, check out our Recruitment Policy The role We are looking to hire a Senior Research Technician join a large-scale project performing deep mutational scanning of membrane
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of Health Science and Technology, one or more PhD stipends in Unsupervised Learning for Medical Image Analysis are available for appointment from November 1, 2026, or as soon as possible thereafter