Level of qualifications required : Graduate degree or equivalent
Fonction : PhD Position
About the research centre or Inria department
The Inria Université Côte d’Azur center counts 36 research teams as well as 7 support departments. The center's staff (about 500 people including 320 Inria employees) is made up of scientists of different nationalities (250 foreigners of 50 nationalities), engineers, technicians and administrative staff. 1/3 of the staff are civil servants, the others are contractual agents. The majority of the center’s research teams are located in Sophia Antipolis and Nice in the Alpes-Maritimes. Four teams are based in Montpellier and two teams are hosted in Bologna in Italy and Athens. The Center is a founding member of Université Côte d'Azur and partner of the I-site MUSE supported by the University of Montpellier.
The PhD position will take place within the framework of an interdisciplinary call between the immuno-oncology and Laënnec (artificial intelligernce for health) Marseille institutes.
The position will be located in the Inria-Inserm team COMPO (COMputational Pharmacology in Oncology), located in the University Hospital of Marseille (AP-HM). The team is composed of mathematicians, pharmacists and clinicians and is a unique multidisciplinary environment focused on developing novel computational tools for decision- making in clinical oncology.
The project will consist in working within the SChISM (Size Cfdna Immunotherapies Signature Monitoring) clinical study, in collaboration with AP-HM and the id-Solution and ADELIS biotechs. The PhD student will be co-supervised by a mathematician (Dr S. Benzekry) and a clinical oncologist (Pr S. Salas).
Early prediction of resistance to immunotherapy is a major challenge in oncology. The ongoing SChISM clinical study proposes an innovative approach based on patented cfDNA (circulating free DNA) quantification methods. Leveraging the longitudinal and quantitative aspect of this data (260 patients in total), we propose to develop mechanistic models of cfDNA joint kinetics with other longitudinal markers and tumor size imaging. Such models embedded within a statistical mixed-effects framework will be calibrated to the population data and subsequently provide individual parameters using Bayesian estimation. Subsequently, we aim to develop integrative machine learning models able to predict outcome (response, PFS and OS) from the combination of these dynamic parameters and other variables available at baseline.
For a better knowledge of the proposed research subject :
 Claret, L. et al. A Model of Overall Survival Predicts Treatment Outcomes with Atezolizumab versus Chemotherapy in Non-Small Cell Lung Cancer Based on Early Tumor Kinetics. Clin Cancer Res, 24, 3292–3298 (2018).
 Khan, K. H. et al. Longitudinal Liquid Biopsy and Mathematical Modeling of Clonal Evolution Forecast Time to Treatment Failure in the PROSPECT-C Phase II Colorectal Cancer Clinical Trial. Cancer discovery (2018) doi:10.1158/2159-8290.cd-17-0891.
 Benzekry, S. Artificial intelligence and mechanistic modeling for clinical decision making in oncology. Clinical pharmacology and therapeutics (2020)
The objectives are to:
1) Establish and validate a mechanistic model of the joint kinetics of cfDNA concentrations and other circulating markers
2) Establish and validate a mixed-effects statistical model for quantification of inter-individual variability
3) Integrate the kinetic parameters together with baseline variables into ML pipelines for early prediction of outcome (response, progression-free survival, 3-years survival, overall survival)
keywords: immunotherapy, cfDNA, mechanistic modeling, machine learning, mixed-effects modeling
Examples of activities:
- Data exploration and visualization
- Biostatistics (e.g. statistical tests, survival analysis)
- Programming (R/python)
- Mathematical modeling of the pharmaco-physio-pathology
- Mixed-effects statistical modeling
- Literature review
- Analyze the requirements of the project partners
- Write synthetic and meaningful reports and scientific publications
Technical skills and level required :
- Excellent data science programming skills (python/R)
- Familiarity with real-world data analysis
- Ideally, experience in mixed-effects modeling
Relational skills :
- Ability to work as a team
- Subsidized meals
- Partial reimbursement of public transport costs
- Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
- Possibility of teleworking (after 6 months of employment) and flexible organization of working hours
- Professional equipment available (videoconferencing, loan of computer equipment, etc.)
- Social, cultural and sports events and activities
- Access to vocational training
- Social security coverage
1982€brut per month (year 1 & 2) and 2085€ brut/month (year 3)
- Theme/Domain :
Computational Neuroscience and Medicine
Statistics (Big data) (BAP E)
- Town/city : Marseille
- Inria Center : CRI Sophia Antipolis - Méditerranée
- Starting date : 2022-10-01
- Duration of contract : 3 years
- Deadline to apply : 2022-06-30
The keys to success
Strong motivation to apply computational methods to concrete health problems
Inria is the French national research institute dedicated to digital science and technology. It employs 2,600 people. Its 200 agile project teams, generally run jointly with academic partners, include more than 3,500 scientists and engineers working to meet the challenges of digital technology, often at the interface with other disciplines. The Institute also employs numerous talents in over forty different professions. 900 research support staff contribute to the preparation and development of scientific and entrepreneurial projects that have a worldwide impact.
Instruction to apply
Defence Security :
This position is likely to be situated in a restricted area (ZRR), as defined in Decree No. 2011-1425 relating to the protection of national scientific and technical potential (PPST).Authorisation to enter an area is granted by the director of the unit, following a favourable Ministerial decision, as defined in the decree of 3 July 2012 relating to the PPST. An unfavourable Ministerial decision in respect of a position situated in a ZRR would result in the cancellation of the appointment.
Recruitment Policy :
As part of its diversity policy, all Inria positions are accessible to people with disabilities.
Warning : you must enter your e-mail address in order to save your application to Inria. Applications must be submitted online on the Inria website. Processing of applications sent from other channels is not guaranteed.