Post-Doctoral Fellow in Epidemiology, Biostatistics, Health Data Science

at  Luxembourg Institute of Health

The Ageing, Cancer, and Disparities (ACADI) Research Unit within the Department of Precision Health, is an international and multidisciplinary team which aims to improve cancer outcomes in older adults by targeting key moments in the cancer journey where inequalities are likely to occur: before diagnosis, during the treatment decision-making process, and the active phase of treatment.
Due to the heterogeneity in health fitness of the older population, a digital decision aid tool based on risk prediction models including patient-related variables, tumor-related variables and geriatric variables to be used in clinical practice can help oncologists identify older patients who would benefit the most from treatment.
We are seeking a postdoctoral researcher to develop and validate models to predict the risk of early death and the risk of toxicity in older adults with cancer using observational data.
The candidate should be willing to spend some time in Oxford, England to conduct some analyses on-site if necessary.
The researcher will work under the supervision of Dr Sophie Pilleron, the head of the ACADI team. They will benefit from expertise from the Deep Digital Phenotyping Lab led by Dr Guy Fagherazzi, Director of the Department of Precision Health and the international network of Dr Pilleron in geriatric oncology, and epidemiology.
The researcher will be encouraged to attend training and conferences and supervise master’s students.

KEY ACCOUNTABILITIES

• Take a lead role in scientific activities
• Participate in research unit meetings & organisation;
• Conduct statistical analyses
• Publish first- and co-authored manuscripts
• Present findings at international conferences
• Prepare and submit applications to national and international funding agencies in order to establish research independence.
• Actively participate in the activities of the group and its research development,

KEY SKILLS, EXPERIENCE AND QUALIFICATIONS

• PhD in health data science, biostatistics, epidemiology or comparable;
• Candidates will have an advantage if they have research experience in cancer, and risk prediction modelling.
• Good writing skills in English.

Please refer the Job description for details