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Dr. Tsilidis is a Senior Lecturer in Cancer Epidemiology in the Department of Epidemiology and Biostatistics of Imperial College. Since January 2020, he is the co-PI of the World Cancer Research Fund Continuous Update Project at Imperial College, which performs evidence syntheses of the diet, adiposity and physical activity associations with risk of cancer development and survival. He also holds an Associate Professor position in Epidemiology at the University of Ioannina School of Medicine in Greece.
He was trained at the University of Athens, where he received a Bachelor's in Nursing and a Master's in Public Health, and at the School of Public Health of the Johns Hopkins University in Baltimore, USA, where he received a Master of Health Science in Biostatistics and PhD in Epidemiology. He performed his post-doctoral training in cancer epidemiology at the University of Oxford in the UK.
He is a molecular epidemiologist with a strong focus on cancer aetiology and prevention. His research focuses on the role of genetic, dietary, metabolic and hormonal pathways in cancer development, prognosis and survival. He is further interested in evidence synthesis methods and applications, Mendelian randomization, pharmaco-epidemiology, and the methodological assessment and correction (via causal inference methods) of systematic errors in the biomedical literature.
He was trained at the University of Athens, where he received a Bachelor's in Nursing and a Master's in Public Health, and at the School of Public Health of the Johns Hopkins University in Baltimore, USA, where he received a Master of Health Science in Biostatistics and PhD in Epidemiology. He performed his post-doctoral training in cancer epidemiology at the University of Oxford in the UK.
He is a molecular epidemiologist with a strong focus on cancer aetiology and prevention. His research focuses on the role of genetic, dietary, metabolic and hormonal pathways in cancer development, prognosis and survival. He is further interested in evidence synthesis methods and applications, Mendelian randomization, pharmaco-epidemiology, and the methodological assessment and correction (via causal inference methods) of systematic errors in the biomedical literature.
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