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, econometrics or another relevant field. You will have substantial relevant research experience in complex trait genetics, a proven ability to code and a strong publication record. If no suitable applicant is
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publications in reputable outlets appropriate to the discipline. Contribute to grant applications submitted by others and develop own research objectives and proposals for funding. The Person Knowledge, Skills
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Experience with controlled laboratory systems Interest in adaptation, climate change or conservation applications Qualifications PhD in ecology, evolutionary biology, or a related discipline (Research
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with applications to attract external research funding and participate in patient and public engagement activities. What we are looking for: Candidates can find a full list of essential and desirable
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About us: The applicant will join the Wellcome-funded Imaging Machine learning And Genetics in Neurodevelopment (IMAGINE) lab, in the Research Department of Biomedical Computing. The post will
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) and fixed term for 2 years. The closing date for applications is noon on 14 April 2026. You will be required to upload a CV and a cover letter as part of your online application. The cover letter should
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for applications is noon on 14 April 2026. You will be required to upload a CV and a cover letter as part of your online application. The cover letter should clearly describe how you meet each of the selection
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essential. The appointment is fixed term for 5.5 months on a part time basis at 44% FTE (16.46 hours per week). Only applications received before midday on Monday, 16 March 2026 will be considered. You will
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'Apply' above. Please ensure that you upload your Curriculum Vitae (CV), a covering letter and publication list in the Upload section of the online application. If you upload any additional documents which
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: Comprehensive personalised Assessment, early Risk Evaluation and clinical management” (HER-CARE) project. The successful applicant will work on the project “Assessing the role of rare germline non-coding genetic