Missions

Develop a data analysis workflow and structure the service offering for users of the GEMELI platform

Activités

* Develop and deploy a metabolomics data analysis pipeline incorporating best practice in bioinformatics, to ensure accurate and reproducible results. He/she will be able to use the team's initial skills in transferring .raw to .mzXML via proteowizard, as well as using MZmine, Workflow4metaabolomics and R packages (Bioconductor, metabolomicsR),
* Integrating new technologies, i.e. adapting and integrating study software, Compound Discoverer 3.3 (ThermoFischer Scientific), as high-resolution data analysis tools to improve the identification and annotation of features (correpsonding to a given retention time and m/z ratio) (XCMS, CAMERA, ROPLS).
* Managing the training of pipeline users on the platform: taking part in training and creating support materials for users of the GEMELI platform in the use of the new workflow and providing ongoing support to ensure that practices are accepted.

Compétences

1. Technical skills in bioinformatics/metabolomics
- Proficiency in metabolomics data processing tools: MZmine, XCMS, CAMERA, ROPLS, FactoMineR, Bioconductor
- Knowledge of standard file formats: .raw, .mzXML, conversion via ProteoWizard
- Ability to develop, adapt and document a reproducible analysis pipeline
- Experience with Workflow4Metabolomics or Galaxy environment
- Use and integration of proprietary software, in particular Compound Discoverer 3.3 (ThermoFisher)
- Proficiency in scripting languages: R (mandatory), possibly Python, Bash
- Knowledge of metabolite identification/annotation standards (m/z, RT, MS/MS)

2. Cross-disciplinary skills
- Ability to formalise complex workflows and ensure their quality, traceability and reproducibility
- Analytical skills, scientific rigour and autonomy
- Excellent ability to document procedures and produce training materials
- Ability to work in a multidisciplinary team (bioinformaticians, biologists, analytical chemists)

3. Training and support skills
- Pedagogy and ability to train non-specialist users
- Design of teaching aids (tutorials, step-by-step guides)
- Experience in user support, technical assistance, post-training follow-up

Desired skills (additional assets) :
- Knowledge of the Open Science ecosystem, FAIR data, or good practice in scientific reproducibility
- Experience in a technology platform / national infrastructure environment
- Fluency in scientific English (written/oral)
- Familiarity with quality procedures (e.g. ISO 9001 or internal procedures)

Contexte de travail

The candidate will work on the GEMELI platform (Grenoble Expertise in Metabolomics and Lipidomics), a cutting-edge technological infrastructure integrated into the Grenoble Health site. GEMELI is developing regionally, nationally and internationally recognised expertise in the field of metabolomics applied to human health, based on the complementary technologies of mass spectrometry (MS) and nuclear magnetic resonance (NMR).
Working closely with academic research laboratories (notably TIMC), hospitals (CHUGA), biomedical innovation players and national (IBISA, RFMF) and European networks, the platform offers analytical services, interpretation services and methodological developments covering the entire value chain, from the raw sample through to bioinformatics analysis and biological data integration.

GEMELI is involved in high-stakes translational research projects related to :
- chronic diseases and multimorbidity,
- infectious and inflammatory diseases
- oncology and central nervous system pathologies,
- personalised and precision medicine.
The future engineer will contribute to this dynamic by implementing bioinformatics analysis pipelines in metabolomics, integrating innovative software solutions (open-source or proprietary such as Compound Discoverer), and providing technical and educational support for platform users. He/she will work in a stimulating environment, at the interface between biology, bioanalysis and data science, at the heart of an ecosystem focused on the integration of omics data, complex phenotyping and artificial intelligence approaches.
This post is in line with the strategy of the Grenoble Health site, which aims to strengthen research and innovation capabilities in order to promote the emergence of patient-centred trajectory medicine, supported by the integrated analysis of health data.

Le poste se situe dans un secteur relevant de la protection du potentiel scientifique et technique (PPST), et nécessite donc, conformément à la réglementation, que votre arrivée soit autorisée par l'autorité compétente du MESR.

Contraintes et risques

1. High cognitive workload
- Analysis of complex data, requiring constant rigour and the ability to stay focused for long periods.
- Handling several projects in parallel, sometimes to tight deadlines.

2. Prolonged work at computer workstations
- Prolonged sitting, exposure to screens.
- Risk of musculoskeletal disorders (MSDs) if ergonomics are not optimal.

3. Adapting to rapid technological change
- Regular monitoring is required to keep tools (software, packages, standards) up to date.
- Need to requalify certain pipelines in line with software updates or community standards (FAIR data, reproducibility, etc.).

4. Working in a multi-actor environment
- Interaction with a wide variety of profiles (researchers, clinicians, technicians, data scientists, novice users, etc.).
- Need to adapt your language and teaching methods to suit the people you are dealing with.

5. Participation in training / support
- Preparation of materials, running sessions, managing questions and user support.