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Postdoc in Genetic Epidemiology – Statistical Genetics | Human Technopole, Milan Build the science that shapes the future of human health. Application closing date: 26.02.2026 Join a place where
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for early-stage cancer using statistics and/or machine learning (including deep learning where appropriate). You will join a vibrant and growing research group of 12 scientists (six postdoctoral researchers
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websites https://www.augusthuanglab.org/ and https://www.khoshkhoolab.com/ . Candidate qualifications include: PhD and/or MD in computational biology, bioinformatics, genomics, or other related fields
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Science including quantitative and qualitative consumer research methodologies, and experience in designing consumer studies in and out-side Denmark. Solid experience in statistical analysis are preferred
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histology or imaging techniques. ⦁ Familiarity with R or other statistical tools for data analysis. The postdoctoral researcher and PhD-student positions are initially limited to 2 and 4 years
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but also in a team you hold a PhD in life sciences (e.g. molecular biology, biochemistry, genomics, computational biology or related areas) you have experience in NGS-based assays and NGS data analysis
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for We are seeking a motivated computational biologist with a passion for cancer genomics and a drive to tackle complex biological questions. Essential: PhD (or studying towards a PhD) in computational
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applications, for example in machine learning and mathematical statistics Participation in the scientific activities of the department, e.g. seminars, workshops and schools organised by the members
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biobanks such as the UK Biobank and AllOfUs. The ideal candidate should hold an MD or PhD, and have a strong background in human genetics and/or statistics, including knowledge of genomewide methods, such as
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Nature Careers | Vancouver South Shaughnessy NW Oakridge NE Kerrisdale SE Arbutus Ridge, British Columbia | Canada | 9 days ago
technology. The postdoctoral researcher will also contribute to the development and validation of identified biomarkers and help assess their potential for CVD risk assessment using statistical analysis. As a