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prostate cancer risk across diverse ethnic groups. This work aims to support more equitable risk stratification in cancer screening programmes. Using simulations based on multistate modelling framework
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modelling and cleansing plans, ensuring alignment of people, processes, and systems. Manage data from start to finish, including planning, execution, and validation. Stakeholder Collaboration: Collaborate
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data models for electronic health records of people with mental disorders, under the guidance of Dr Osimo and Prof Murray at Cambridge, and a line manager to be selected at Akrivia Health. The aim
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negative mammogram. This role provides scope not only to support these evaluations but also to develop and test your own models. As part of the role, you will help expand CC-MEDIA by collecting and curating
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and maintain laboratory neurodevelopmental models from stem cell lines. The aim of the research is to understand developmental sex differences of the brain, specifically towards revealing
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will be addressed using a series of behavioural and electro-physiological experiments with Cochlear Implant users, as well as comparing the outcomes with predictions from existing computational models
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would be advantageous. Experience focused on novel semiconductor devices or training ML models is not particularly relevant for this role. It should be possible to take someone with extensive experience
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across ELFT and identify key stakeholders working in maternal child health, ii) contribute to evidence synthesis on models of care for maternal and child health in low resource settings locally and
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computational scientists to develop advanced algorithms and models. Research and validate potential biomarkers associated with breast cancer progression, treatment response, or patient outcomes, using
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contribute to ongoing cancer risk modelling projects within the Centre for Cancer Genetic Epidemiology (CCGE), based in the Department of Public Health and Primary Care. They should have a strong understanding