Research engineer Statistical analysis of longitudinal medical data

Research Engineer Statistical Analysis of Longitudinal Medical Data

Level of Qualifications Required:

Graduate degree or equivalentFunction:

Temporary scientific engineerContext

You will work in the context of the project REWIND (pRecision mEdecine WIth longitudinal Data), a multicentric project (Paris, Bordeaux, Lyon, Grenoble, Nice) granted via the “Investissement d’avenir” PEPR Santé Numérique. The project will focus on the development of new mathematical and statistical approaches for the analysis of multimodal multiscale longitudinal data. These models will be designed, implemented as prototypes, and then transferred to an easy-to-use, well-documented platform where researchers from diverse communities, particularly physicians, will be able to analyze their own datasets. The project will allow the development of a new generation of decision support systems, which will help clinicians at the bedside to make more informed decisions for the patient. They will contribute to the development of precision medicine in several key areas.In this context, you will work in two teams: HeKA (Inria-Inserm-Université Paris Cité) and ARAMIS lab (Inria, CNRS, Inserm and Sorbonne Université). HeKA is located at the PariSanté Campus (https://parisantecampus.fr), while the ARAMIS lab is located at the Paris Brain Institute (https://institutducerveau-icm.org). While HeKA aims at developing methods, models, and tools to create, evaluate and validate learning health systems, ARAMIS lab is dedicated to the development of new computational approaches for the analysis of large neuroimaging and clinical datasets.You will be strongly involved in the scientific aspects of the work, such as discussion of methodological issues and interpretation of results. You will interact locally with PhD students, postdoctoral fellows, and engineers. You will take part in the communications and publications resulting from the use of the software.Assignment

The ARAMIS lab develops the open-source software Leaspy, a Python library for the statistical analysis of longitudinal data, particularly medical data that comes in the form of repeated observations of patients at different time points. Leaspy allows users to easily fit various models to large-scale clinical studies consisting of clinical scores, cognitive assessments, physiological measurements, or imaging-derived data. Leaspy aims at recombining these series to reconstruct the long-term spatio-temporal trajectory of disease evolution. Each patient can then be positioned relative to the group-average timeline, in terms of both the temporal and spatial differences. Future observations as well as virtual patient trajectories can then be simulated. Leaspy is distributed freely to the scientific community and has users worldwide. It has been used to produce high impact medical publications that have advanced the understanding of neurodegenerative diseases such as Alzheimer’s disease, fronto-temporal dementia, and amyotrophic lateral sclerosis.Main Activities

You will be in charge of the:development of new features (implementation of new models, algorithms, metrics, visualizations),software maintenance,user support and animation of the community.In addition, you will be presenting the software at international scientific conferences and other events (organized for instance by Inria, ICM, CNRS…). Finally, you will contribute to ambitious medical studies by using Leaspy on large databases of patients, contributing to the interpretation of results and providing assistance to users (internal to the lab and external collaborators).Skills

PhD degree or master + experience in the field of statistical analysisStrong programming skills in PythonExperience working with Git/GitHub on open-source projects would be a plusExcellent relational and communication skills to interact with users and lab membersGood writing skills (documentation, website, scientific articles)Benefits Package

Partial reimbursement of public transport costsLeave: 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 (after 12 months of employment)Professional equipment available (videoconferencing, loan of computer equipment, etc.)Social, cultural and sports events and activitiesInstructions to Apply

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.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.

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