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Centre de la science des données biomédicales
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Join Us
The Biomedical Data Science Center at CHUV brings together clinicians, data scientists, and researchers to advance biomedical research through data science and AI. We welcome motivated candidates at all career stages to join our growing and collaborative environment. Open Positions We currently have
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Legal notice
These legal notices apply to all websites operated by the Centre hospitalier universitaire vaudois (CHUV). Limitation of Liability The information provided on all CHUV websites is intended to support, not replace, the relationship between patients or website visitors and healthcare professionals. Al
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Contact us
Whether you wish to learn more about our projects or need support from our specialists, feel free to contact us using the form below. Get in touch for: Collaborating with us We supply data, computational resources and person-hours to cooperate in the realization of your research. Moreover, we are ha
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About us
Background The digital revolution in healthcare: challenges and opportunities Breakthroughs in biotechnology and information technology are redefining modern medical practice. The rise of increasingly powerful computing resources, the development of cutting-edge AI algorithms, and the massive accumu
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Terms of Use
This contact form is intended for your questions or suggestions related to our Institution. Please take note of the following points before sending us a message: Requests for Medical Advice and Confidential Information For confidentiality and to ensure the quality of your care, we are unable to resp
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Impressum
This website is operated by the Centre hospitalier universitaire vaudois (CHUV). The CHUV is a public institution of the State of Vaud and is part of the Department of Health and Social Action. As such, this website is funded by the State of Vaud and does not receive advertising revenue. Editorial B
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Fellay Group
The Fellay group conducts translational genomics research to demonstrate the clinical value of human genome analysis in medicine, focusing on polygenic risk scores, pharmacogenomics and genomic data integration in healthcare. This group, led by Prof. Jacques Fellay, associate professor at the Facult
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Perturb
We create predictive models that go beyond observation to simulate how biological systems respond to drug, genetic or immunotherapy perturbations, supporting virtual experimentation that accelerates hypothesis generation and therapeutic prioritization. In the Perturb theme, we develop AI/ML models t
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Rapsomaniki Group
The Rapsomaniki Group develops AI and machine learning methods for biomedicine, with the vision to transform complex biomedical data into mechanistic models of disease and to guide precision intervention across scales- from molecules and cells to tissues, patients, and therapeutic outcomes. Our rese
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