Mots-Clés

cancer genomics epigenetics multiomics early detection cancer diagnosis

Description

Postdoctoral Researcher in Data Science/Bioinformatics for Cancer Genomics

Duration: 2 years, renewable
Location: INSERM U981, Gustave Roussy Cancer Campus, Grand Paris, France

Project Overview

We are seeking a highly motivated postdoctoral researcher or experienced data scientist to join our interdisciplinary team at Gustave Roussy, Europe’s leading cancer centre. The successful candidate will contribute to an innovative project focused on improving early detection of breast cancer through advanced genomic analysis on minimally invasive samples.

This project is a collaborative effort involving the Interception Programme, the Computational Oncology Laboratory, the Genomics Platform, and the Biostatistics Department at Gustave Roussy, together with Unicancer and École CentraleSupélec. The successful candidate will be working under the supervision of Dr. Bruno Duso, clinician-scientist in charge of the Interception Translational Research Laboratory (ITRL), hosted by the INSERM U981 unit (Molecular predictors and new targets in oncology, head Prof. Fabrice André), in collaboration with Dr. Suzette Delaloge – director of the Interception Programme, Dr. Elsa Bernard – Head of the Computational Oncology Laboratory, Dr. Damien Drubay – senior data scientist at the biostatistics office of Gustave Roussy and the INSERM U1018 unit (Oncostat team, head Prof Stefan Michiels), Philip East – head of the Clinical Discovery Bioinformatics group within IHU PRISM – and in close collaboration with Prof. Paul-Henry Cournède – director of the MICS Laboratory and director of Research at École CentraleSupélec.

The project aims to develop a machine learning model to predict for the advent of a breast cancer within the next three years, which integrates multiple layers of genomic data – including DNA (hydroxy)methylation profiles, transposable element activity, structural variants, and fragmentomics – with standard clinical data and PGS from saliva samples. Using Oxford Nanopore Technology (ONT) long-read sequencing, the research will analyse samples from the MyPeBS trial, the largest randomised study evaluating risk-based breast cancer screening in Europe.

Key Responsibilities

• Process and analyse ONT sequencing data from saliva DNA samples in collaboration with the Genomics Platform team.
• Integrate (hydroxy)methylation profiles, SVs, and fragmentomics into comprehensive genomic analyses.
• Develop and implement machine learning models in partnership with Prof. Paul-Henry Cournède’s group at École CentraleSupélec.
• Collaborate with biostatisticians and clinicians to validate findings using internal and external cohorts.
• Prepare and publish high-quality research papers in peer-reviewed journals.
• Present findings at scientific conferences and seminars.

Qualifications and experiences:

• Ph.D. in Bioinformatics, Computational Biology, Data Science, or a related field. Candidates with a Master’s degree and at least 3 years of relevant work experience are also welcome to apply.
• Experience of analysing different types of high-throughput sequencing applications within a research environment.
• Excellent R and/or Python skills with knowledge of available packages and resources.
• Experience with machine learning techniques and tools.
• Familiarity with ONT sequencing is an advantage.
• Good Linux and HPC skills.
• Excellent problem-solving skills and ability to work independently and collaboratively within a scientific discovery environment.
• Strong written and verbal communication skills in English; knowledge of French is a plus.
• Familiarity with cancer biology would be desirable.
• Familiarity with the application of statistical techniques to biological data.
• Experience of software development processes and tools.

Team and Supervision

You will be joining a dynamic team, working closely with experts from:

• Interception Programme: an initiative aimed at early detection and prevention of cancer by identifying and intercepting precancerous conditions combining fundamental research and clinical interventions.
• Clinical Discovery Bioinformatics: Data analysis and management of patient derived omics data sets.
• Cancer Data Science Program: including the Computational Oncology Laboratory at Gustave Roussy and the Biomathematics Team at École CentraleSupélec. Focuses on leveraging data analytics, machine learning, and computational methods to enhance cancer research, diagnosis, treatment, and overall patient care.
• Genomics Platform of Gustave Roussy: specialised in advanced genomic sequencing technologies.
• Biostatistics Office of Gustave Roussy / Oncostat team (INSERM U1018): focusing on the development of statistical and machine learning methods for the evaluation of precision medicine in oncology based on the level of evidence.
• Unicancer: a federation of French cancer centres contributing with clinical expertise.

What We Offer

• Opportunity to work on a cutting-edge project with significant clinical impact.
• Access to state-of-the-art facilities and collaboration with leading experts in cancer research.
• Supportive research environment fostering professional development.
• Initial fixed-term 24-month contract, with possible extension. Competitive salary based on experience and institutional guidelines.

How to Apply

Interested candidates should submit the following documents:

• A cover letter describing your research interests and suitability for the position.
• Curriculum vitae including a list of publications.
• Contact information for at least two academic references.

Please send your application as a single PDF file to bruno.achutti-duso@gustaveroussy.fr ,elsa.bernard@gustaveroussy.fr and (philip.east@gustaveroussy.fr) with the subject line “Postdoc Application – Data Science for Cancer Genomics.” For inquiries about the position, please contact Dr. Bruno Duso (bruno.achutti-duso@gustaveroussy.fr) and/or Dr. Elsa Bernard (elsa.bernard@gustaveroussy.fr), Philip East (philip.east@gustaveroussy.fr) Join us in our mission to advance cancer prevention and improve patient outcomes through innovative research!