Mots-Clés

Deep learning - multi-omics integration

Description

We are seeking a candidate for a PhD position funded by a French CIFRE fellowship.

The candidate will share their time between Sanofi (under the supervision of Dr Franck Augé/France & Dr Milad Rafiee Vahid/US) and the university of Paris-Saclay (under the supervision of Pr Blaise Hanczar and Dr Farida Zehraoui in the lab of computer science, bioinformatics and complex systems IBISC) and they will be enrolled in the Doctoral School STIC at Université Paris-Saclay (Univ. Evry). 

The project is about the application of deep learning for phenotype prediction from multi-omics data. It focuses on i) identifying the suitable architectures for each omics source; ii) Integrating multi-omics data using neural network based embeddings; iii) interpreting the constructed model for biomarkers identification or patient stratification.

The project will be developed on both public datasets (pan-cancer) and the MMRF/CoMMpass data set (multiple myeloma).

We are seeking a candidate with master degree (“diplôme de master”, “école d’ingénieurs”) or equivalent in Computer science or applied mathematics, and:

• Strong background in machine learning;
• Good knowledge in machine/deep learning framework (scikit-learn, Tensorflow, Pytorch);
• *Experience in bioinformatics (omics data analysis) is a plus;
•  High motivation to work in both academic and industry environments.