Postdoctoral position: Federated Statistical Learning for Large-scale Biomedical Applications

Christophe Bobineau
Calendar
When:
31/01/2022 – 01/02/2022 all-day
2022-01-31T01:00:00+01:00
2022-02-01T01:00:00+01:00
Jobs

Offre en lien avec l’Action/le Réseau : – — –/Doctorants

Laboratoire/Entreprise : EPIONE group – Inria Sophia Antipolis
Durée : 18 months
Contact : marco.lorenzi@inria.fr
Date limite de publication : 2022-01-31

Contexte :
The project Fed-BioMed focuses on methodological and technical advances towards the development of a novel generation of federated learning methods for the analysis of private and large-scale multi-centric biomedical data. The project has a specific focus on the efficient federation of frameworks robust to data heterogeneity and uncertainty, and tackles the following scientific challenges:

– Methodological. Extending the federated paradigm to novel scalable approaches to probabilistic modeling and prediction from siloed data.
– Technical. Developing our federated learning framework through a self-contained system that can be securely deployed across different centers and collaborators (fedbiomed.gitlabpages.inria.fr).
– Translational. Demonstrating federated learning on two applications: 1) Discovering novel genetic underpinnings of neurological and psychiatric disorders, and 2) Prediction of response to immunotherapy from the analysis of federated lung imaging data.

Sujet :
During the project the candidate will:

• Develop learning methods for federated analysis for private and distributed data;
• Deploy advanced statistical learning methods into a wide range of biomedical/clinical applications;
• Interact with INRIA researchers and engineers, and participate to the scientific life of the team;

Profil du candidat :
We look for a motivated candidate holding a PhD in a domain among computer science, biomedical engineering, and related fields.
A proven track record of publications and presentations to scientific events is required.

Formation et compétences requises :
Demonstrable experience in some of the following topics (the more the better):

– Statistics, Bayesian Modeling;
– Optimization, Distributed Computing;
– Python and PyTorch/TensorFlow;
– Biomedical Data Analysis;
– Signal Processing;

Strong communication abilities are necessary, as well as motivation in taking responsibilities (e.g. supervision, organization of scientific events).

Adresse d’emploi :
Epione team (Inria), located in the tech park of Sophia Antipolis (France).
Email: marco.lorenzi@inria.fr

Document attaché : 202111220859_job_offer-PostDoc-FedBioMED_v2.pdf