Centre de recherche du CHU de Québec-Université Laval



, Quebec


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488 days ago Apply now

The Centre de recherche du CHU de Québec-Université Laval (axe Oncologie) is seeking faculty candidates for an assistant professor position at the Faculty of Medicine of Université Laval. Candidates must be conducting or aiming to develop innovative and interdisciplinary research program focusing on solving important problems in cancer biology, prevention and treatment with a major emphasis on bioinformatics, system biology, data science, and/or machine learning. The new faculty member will have the opportunity to join established research groups including the Centre de recherche sur le cancer de l’Université Laval (CRC), the Centre de recherche en données massives (CRDM) as well as the Institut intelligence et données (IID). In the last years, our institution benefited from significant investments including a new state-of-the-art Tier 3 data/computing center, led by a dedicated IT team (VALERIA) which manages our institutional data lake. We also benefit from a data-driven research platform (PULSAR), allowing researchers to share, reuse, link and increase the visibility of their data in compliance with the FAIR principles. Therefore, the new faculty member will have access to a cutting-edge data research infrastructure providing easy access, flexibility and reliability for data-driven research projects.
Candidates must have a Ph.D. in a relevant field of study, a postdoctoral or comparable experience, a demonstrated record of research excellence and should have made important contributions to their field. Preference will be given to applicants with an outstanding record conducting team science and collaborative research.
Salary support and start-up funds are available starting in the first half of 2023. High profile candidates will have the opportunity to apply for Canada Research Chairs.
Applications, including a summary of proposed research program (3 pages), a curriculum vitae and the names and addresses of two referees, should be sent before November 25th 2022 to the recruitment committee (
About Centre de recherche du CHU de Québec-Université Laval
Our vision: innovate to prevent and treat
In a world where healthcare needs are constantly and rapidly rising, and where scientific innovation, technological development and artificial intelligence hold the lion’s share of society’s collective wealth, the Centre de recherche du CHU de Québec-Université Laval (CRCHUQc-UL) already stands out due to the quality and originality of its different teams of researchers in basic as well as translational, clinical, epidemiological and populational research. In an environment that is constantly evolving and faced with the growing complexity of acquiring knowledge and new technology, researchers must show more solidarity and exploit all available resources regarding their respective scientific competencies, as well as the various methods of funding. To maintain its remarkable momentum, our research center must not only continue to advance in each of the seven axes where it has made its mark, but also promote collaboration between these axes and the dissemination of findings that have made the reputation of its researchers. Join the CRCHUQc-UL and become part of the largest French-speaking health research centre in North America.
About axe Oncologie
Our vision: implement precision oncology as a standard of care
The mission of axe Oncologie of CRCHUQc-UL is to bring clarity and resolution to complex scientific problems related to cancer, for the benefit of patients and society. Meeting this challenge is made possible thanks to our diverse and multidisciplinary research expertise that span the entire spectrum of health sciences. This includes basic research in cellular and molecular biology and medical physics, clinical research, as well as physical and psychosocial health care and public health interventions. The research programs pursued within the division are grouped into three themes: 1) Biology, etiology and prevention, 2) Screening, diagnosis, prognosis and treatment, 3) Survival, quality of life and health services.





system biology

data science

machine learning


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