Mots-Clés

métabolisme intelligence artificielle microbiome ecg

Description

Missions

A PhD scholarship funded by CNRS is available at the European Genomic Institute for Diabetes (UMR 8199 CNRS, INSERM, Institut Pasteur de Lille, CHU Lille, Université Lille) in the “Microbiome and Metabolome and Metabolic Diseases” group and Integrative Metabolomics and Phenomics for Translational and Precision Medicine (IMPACT-PM) platform supervised by Prof. Marc-Emmanuel Dumas, in Lille, France.

This PhD studentship is part of the International Research Project in Integrative Metabolism between CNRS, the University of Lille and Imperial College London. The PhD Student will collaborate with researchers at Imperial College London and travel regularly to Imperial for training and research.

Activities

The project focusses on the role of the microbiome on cardiac aging. The PhD student will develop machine learning models to evaluate cardiac age from raw electrocardiogram (ECG) waveforms, epigenetic age from DNA methylation (DNAm), and metabolomic age from ultra-high performance liquid chromatography coupled to high-resolution mass spectrometry (UHPLC-HRMS) metabolomic data.

The successful candidate will gain training and will work towards developing linear and machine learning multimodal models available from the various datasets available in the lab for >12,000 patients:

• Management of project data

• Development of machine learning pre-processing methodologies for raw ECG waveforms

• Development and implementation of DNA methylation epigenetic clocks and metabolomic clocks

• Implementation of ML/AI-based multimodal analyses and visualisation

He/She will be responsible for data processing and scientific dissemination of results (drafting of scientific articles in English and participation in conferences). The successful candidate will play a role in influencing the project: design of workflow, optimisation and benchmarking, prioritisation and interpretation of results.

Skills

The candidate will:
• hold a MSc or MEng. in computational biology/medicine, bioinformatics, machine learning, AI or similar subject

• be an expert in computational metabolomics

• be an expert in machine learning, ideally applied to electrocardiograms

• have experience in developing aging models

• have knowledge of univariate and multivariate statistics

• have knowledge of data science software, R. Python, etc…

• master the English language (written and spoken)

• have an interest in multidisciplinary work

• demonstrate autonomy, rigor, critical thinking, problem solving and ability to work within an international team

Work Context

The researcher will join the “Metabolome, Microbiome and Metabolic Diseases” group at U1283/UMR8199 EGENODIA (head: Philippe Froguel) at the European Genomic Institute of Diabetes (EGID, recognised by a ‘Laboratory of Excellence’ award), whose research objectives are to study the microbiome and its metabolic output to identify novel microbial compounds and characterise their bioactivities in metabolic diseases. The Institute provides an excellent intellectual environment and most of the infrastructure required to carry out the project, with direct access to state-of-the-art platforms including metabolomics by high-resolution mass spectrometry (IMPACT-PM), high-throughput sequencing (LIGAN-PM, ‘Equipment of Excellence’ platform award), animal facilities with a small imaging platform and a core facility for metabolic studies (metabolic cages, treadmill, CTscan, PET scan, MRI), cell imaging facility (confocal microscopy, electron microscopy), flow (INFLUX BD) and mass (CyTOF) cytometry. More specifically, the candidate will be part of the ‘Accueil de Talents’ project awarded to Prof. Dumas and funded by the I-Site ULNE, Région Hauts-de-France and Métropole Européenne de Lille and the IHU2 Precidiab. The researcher will strongly interact with colleagues within the group, the Institute and international collaborators at Imperial College London, through the “CNRS-Imperial International Research Project in Integrative Metabolism” led by Prof. Dumas.