ML-Driven SAF Database & Property Predictor

IFP Energies Nouvelles Group; Rueil-Malmaison; On-site; EUR 10,000 - 15,000; Full time

Job summary

IFP Energies Nouvelles Group seeks a motivated intern to develop a sustainable aviation fuels database and build ML models for property prediction. You will work on data architecture, APIs, and a user interface to enable efficient data storage and retrieval.

The role includes data integration from literature and experiments, plus exploring advanced data-driven techniques for uncertainty and knowledge management. French or English communication required.

Qualifications

• Bac+4 or Bac+5 in Computer Science, Data Science, or related fields.
• Proficiency in relational database, machine learning, and AI tools.
• Familiar with API, Web UI Design, GitLab.
• Ability to code and write in English.

Responsibilities

• Database development for a fuel-property dataset and ML-ready pipelines.
• Integrate, curate, and validate experimental and literature data with traceability.
• Develop ML-based predictions of property data and fuel blends.
• Explore data-driven methods, including uncertainty quantification and active learning.

Skills

Relational databases

Machine learning/AI tools

APIs & Web UI

English proficiency

Education

Bac+4/5 in Computer Science or Data Science

Tools

GitLab

API design

Web UI Design

Job description

IFP Energies Nouvelles Group seeks a motivated intern to develop a sustainable aviation fuels database and build ML models for property prediction. You will work on data architecture, APIs, and a user interface to enable efficient data storage and retrieval.

The role includes data integration from literature and experiments, plus exploring advanced data-driven techniques for uncertainty and knowledge management. French or English communication required.