Are you an enthusiastic, ambitious, recently graduated PhD with a passion for applying state-of-the-art data-analytical methods to adequately answer clinically/societally relevant research questions to ultimately have impact on cancer care and prevention? And do you feel at home in a cross-disciplinary setting? Then we are looking for you!
We have a four-year Assistant Professor-level position available in our Cancer Research program at the Julius Center for Health Sciences and Primary Care (a division of the University Medical Center Utrecht) to strengthen and complement our team of researchers.
Your direct colleagues will be a team of cancer researchers with a solid background in (clinical) epidemiology and health sciences. We are embedded in a strong network with clinical and translational cancer scientists within the University Medical Center Utrecht and beyond. These collaborations span all phases of cancer research from (very early) translational to confirmatory and guideline-changing, and many involve novel biomarkers to inform and improve clinical decisions. You will contribute to these ongoing collaborations and will be encouraged and mentored to pursue new lines of research and to seek corresponding funding, allowing you to become an independent researcher.
You will need to be able to work as a team-player, with a keen interest in bringing your own expertise to bear to let a research team thrive. This also means taking the initiative to share your knowledge and expertise with other researchers to improve the skill-set of the entire team.
Besides data-analysis of small and large datasets, visualization, reporting research findings, and applying for funding, you will participate in various (data-science) meetings, and will contribute to teaching (for instance within our MSc Epidemiology program).
You will be appointed at the Cancer Epidemiology Team of the Department of Epidemiology within the Julius Center for Health Sciences and Primary Care of the UMC Utrecht. We have many ongoing national and international collaborations, and participate in various advisory boards and committees, and in teaching. As a team we particularly focus on research to optimize cancer survivorship care (emphasizing lifestyle interventions such as physical activity and nutrition), prevention, (early) diagnosis, screening, and treatment, and the evaluation and translation of cancer biomarkers. We are currently a team of three full Professors, one Associate Professor, three Assistant Professors, and over 15 internal and external PhD students. Your supervisor will be Sjoerd Elias, Associate Professor of Clinical Epidemiology.
Our ideal candidate is a researcher recently graduated with a PhD in a relevant field, who is capable of applying advanced data-analytical techniques from both classical statistics (e.g. time-varying survival analysis, mixed models, joint models for dynamic prediction) as well as machine learning methods (e.g. random forests, neural nets). The ability and drive to master and implement novel methods when they are needed to answer a particular research question will be highly valued.
You can work well independently, have excellent skills in R and are accurate and able to manage multiple projects at the same time. You also have excellent English writing and communication skills and the ability to effectively convey your expertise to researchers outside your field. A (bio-)medical background and successful experience with (contributing to) grant applications will be appreciated.