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

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.

What we offer

Researchers have the opportunity to work in an interdisciplinary & international scientific environment, benefitting from diverse exchanges with other students and scientists in and across the department;  
An environment allowing further training in a variety of health-related domains, fostering the acquisition of transferrable skills around presentation & communication skills, scientific English, and statistics.  

Instructions to apply

The applicant must submit the following material in English through the dedicated system:

• a curriculum vitae mentioning your educational background, and professional experiences and the contact for 2 persons of references we can contact.
• a list of your publications
• a cover letter where the applicant MUST answer the following questions: What motivates you to apply for this position? / What is your experience in risk prediction modeling?

For a fair recruitment process, please, DO NOT attach or include any headshot.
Incomplete applications and those that do not address the questions above will not be considered.

Gender Equality

The LIH is an equal opportunities employer. We are fully committed to removing any discriminatory barrier related to gender, and not only, in recruitment and career progression of our staff. 

The LIH is attentive to gender representation among its leadership staff and aims to eliminate obstacles to the recruitment and promotion of female leaders and their career development.