Chronic inflammatory diseases endotyping Researcher (M/F)

The  Inria University of Lille centre, created in 2008, employs 360 people  including 305 scientists in 15 research teams. Recognised for its strong  involvement in the socio-economic development of the Hauts-De-France  region, the Inria University of Lille centre pursues a close  relationship with large companies and SMEs. By promoting synergies  between researchers and industrialists, Inria participates in the  transfer of skills and expertise in digital technologies and provides  access to the best European and international research for the benefit  of innovation and companies, particularly in the region.

For more  than 10 years, the Inria University of Lille centre has been located at  the heart of Lille's university and scientific ecosystem, as well as at  the heart of Frenchtech, with a technology showroom based on Avenue de  Bretagne in Lille, on the EuraTechnologies site of economic excellence  dedicated to information and communication technologies (ICT).

The position will take place in a pluridisciplinary team composed of mathematicians, data scientists, clinicians; a unique multidisciplinary environment focused on developing novel computational tools for chronic inflammatory diseases (CID) to better understand them and the applied treatments. The person to be recruited will benefit from a secured access to large local hospital repository composed of multi-omics data, to additional large European databases and to the required computing resources. The proximity with top level  medical  researchers in the domain will allow for a fine exploration of this mass of clinical data. 

The goal of this position is to develop innovative methods to characterize endotypes of chronic inflammatory diseases (CID) based on the integrative analysis of patients combining clinical and follow-up data (highly heterogeneous information) and multi-omics profiles (high-dimensional information). This will  allow to improve the CID nosology.

Main activities:

• Review of the literature
• Benchmark of existing methods
• Development of novel supervised and non supervised clustering algorithms for multiomic data
• Interactions with the biological and clinical partners
• Supervision of data scientists (research engineers, phd students and postdoctoral fellows)
• Test and validation

 Additional activities:

• Continuous integration / continuous deployment of the code
• Data visualization
• Statistical reporting to the partners

Technical skills and level required :

• Strong background in statistics and machine learning
• Hands-on experience with real-world medical data analysis
• Experience in computer vision is a plus
• Strong motivation for medical and societal applications of computational methods
• Knowledge of biology and/or medicine is a plus
• Ability to work both independently and as a team, good relational skills
• Excellent programming skills in a scripting language (R and/or Python)

 Additional:

• English speaking
• Academic writing skills
• Oral presentation skills

• 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 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

According to the profile