The challenge is to analyze these BIG DATA to answer clinical and biological questions by using appropriate statistical methods. With data on the machinery of a cell to the clinical status of individuals in any circumstances including in clinical trials, new tools are needed to translate information obtained from complex systems into knowledge. This has led to the field of « systems biology » and « systems medicine » by extension, which naturally takes place in the context of translational medicine that links clinical and biological research.

Human-to-human transmission of Ebola virus in West Africa was interrupted in 2016 but the risk of re-emergence of the disease is real. Thus, efforts to develop a safe and effective vaccine against Ebola virus disease with a durable prophylactic effect in communities must continue. The Partnership for Research on Ebola Vaccinations (PREVAC) is an international consortium including the French Institute of Health and Medical Research, the London School of Hygiene & Tropical Medicine, the US National Institutes of Health, health authorities and scientists from Guinea, Liberia, Mali and Sierra Leone, a non-governmental organisation (Alliance for International Medical Action), and Merck, Johnson & Johnson and Bavarian Nordic companies.
The PREVAC trial is a phase IIB, randomised, placebo controlled, multicentre trial evaluating the safety and immunogenicity over 12 months of three vaccine strategies in children and adults. Participants are randomised to one of five groups: (i) vaccination with Ad26.ZEBOV prime and MVA-BN-Filo boost, (ii) vaccination with rVSVΔG-ZEBOV-GP prime and a boost of the same vaccine, (iii) vaccination with rVSVΔG-ZEBOV-GP vaccine without boost, (iv) placebo group 1 and (v) placebo group 2. Preliminary phases started in Liberia and Guinea in March 2017; the main phase of the trial evaluating the five regimens begun in Liberia, Guinea Sierra Leone and Mali in April 2018 with an enrolment targets of 1,400 adults and 1,400 children.
The PREVAC-UP trial consists in a long term follow-up of patients included in the PREVAC trial to determine (i) the long-term immunogenicity and safety and (ii) durability of humoral and cellular immune responses of Ebola vaccine regimes over 60 months. In this postdoc, we propose to address these two question using mathematical modeling and statistics.

The SISTM (Statistics in Systems and Translational Medicine) team directed by Pr. Rodolphe Thiébaut is involved in PREVAC and PREVAC-UP and had been also involved in many international consortium for EBOLA, ie. EBOVAC1 and EBOVAC3 and coordinates EBOVAC2. In this context one of its main goal is to conduct the analysis and the modelling of the immune response to the Ebola vaccine strategy, using data including immunological substudies recording many biomarkers (cell phenotype, functionality, gene expression, antibody titers...).
SISTM is a team belonging to INSERM U1219 Bordeaux Population Health and INRIA Bordeaux Sud-Ouest research institutes. The group is dedicated to the analysis and the modelling of the data generated in epidemiology and medicine with a special focus on vaccines and immune interventions in HIV and other infectious diseases. Its expertise is mainly in biostatistics with a special emphasis on dynamical models based on ODE and statistical learning using moderately high dimensional data.

The main objective of this postdoc position will be to use the data gathered through the PREVAC/PREVAC-UP trials to build and fit a model of the immune response to the Ebola vaccine in order to better characterize the response (duration) and better understand the mechanism of its establishment. Model estimation will be performed using maximum likelihood approach as implementer with the SAEM algorithm, for example in the MONOLIX software of the Lixoft suite. Methodological development will consist in building a series of model building strategies.

The candidate should hold a PhD in mathematics, physics or statistics. We are looking for a highly motivated candidate with an outstanding potential and a strong background in statistics and a deep interest in immunology and biological application. Proven experience in R language is required. The ideal candidates are able to work effectively as part of a team, but also to develop and pursue independent ideas. The successful candidates are expected to conduct innovative research at the highest international level.
Experience in modelling and applications in biology is highly recommended and previous work in
immunology/Vaccinology, systems biology will be highly appreciated.
The expected starting date can be as soon as possible.

Salary will follow Inserm rates and can be negotiated to be higher depending on previous experience and skills.