Centre Hospitalier Universitaire Vaudois
MD-PhD Position in Cardiovascular Prevention, Doctoral Assistant
📍 Lausanne
Role and responsibilities
The PhD candidate is expected to propose and develop an original, hypothesis-driven research project within SwissCardIA, targeting one or several of these open questions, in alignment with their personal expertise and scientific interests. The project should demonstrate clear scientific ambition, methodological rigor, and potential impact on cardiovascular prevention. The candidate will be fully embedded in the research activities of the SwissCardIA cohort. All activities, including medical assessments, are conducted within a research framework and contribute directly to data generation and scientific output. Activities include: Participation in participant recruitment, follow-up, and study conduct; Conduct and supervision of medical study visits as part of standardized research data collection; Review and interpretation of clinical reports and cardiovascular imaging results in accordance with the study protocol and GCP; Contribution to the medical and scientific oversight of cohort operations; Development and execution of an original PhD research project based on the SwissCardIA data; Advanced statistical data analysis; Critical literature reviews and meta-analyses; Active participation in scientific dissemination, including the preparation of abstracts, presentations at national and international conferences, and publications in peer-reviewed journals; Contribution to academic training and higher education, including involvement in the co-supervision of Master’s thesis students and support of research training activities within the group; Close collaboration with cardiologists, radiologists, epidemiologists, engineers and data scientists.
Team / description
Lausanne University Hospital (CHUV) is one of five Swiss university hospitals, and a leading institution in clinical care, medical research and academic training. The Cardiology Service at CHUV conducts patient-oriented research with direct clinical and public health impact, and offers a dynamic academic environment with strong methodological ecosystem and access to an extensive national and international research network. This PhD position is embedded in SwissCardIA, a large, prospective, population-based cohort study dedicated to individualized primary prevention of coronary atherosclerotic disease. SwissCardIA will recruit n=2’000 asymptomatic, statin-naïve adults aged 50-69 years from the general population and combine detailed clinical and socio-demographic phenotyping, quantitative coronary CT angiography and complementary cardiovascular imaging, longitudinal lifestyle monitoring using wearable devices, and advanced blood-based biomarkers, including multi-omics and genetic risk scores. This study is a collaboration between the Cardiology service at CHUV and data scientists at École Polytechnique Fédérale de Lausanne (EPFL), enabling the integration of advanced biostatistics and AI-based approaches for the development of next-generation risk prediction frameworks.
Qualifications and Skills
Medical Doctor (MD) with a Swiss federal medical diploma or an equivalent degree recognized in Switzerland, eligible to practice medicine in Switzerland
Knowledge of Good Clinical Practices
Excellent written and oral communication skills in French
Good written and oral communication skills in English (C1 level or above)
Strong skills in academic research (literature review, etc)
Strong interest in biostatistics, epidemiology, or data science applied to medicine
Ability to work independently and collaboratively in a multidisciplinary team
Applicants are expected to demonstrate relevant experience, ideally supported by a scientific track record, in one or more of the following areas: Cardiovascular prevention or public health, Cardiovascular imaging, Lifestyle research (physical activity, sleep, nutrition), Precision medicine, Wearable technologies and digital health, Advanced biomarkers (multi-omics), Predictive modelling or machine learning in biomedical research