Research Engineer specializing in the reusability of data science pipelines and the assessment of their environmental impact (M/F)

Job Description

Missions

The research engineer candidate will have three objectives: Represent pipelines in the MoMa model and study their mapping to vector databases. Generate additional pipelines in DataGEMS use cases. Study pipeline composability. Develop and implement criteria for assessing the environmental impact of pipelines. Integrate these criteria into the pipeline database.

Activity

Analyze and model data science pipelines integrating AI, machine learning, and advanced analytics. Study their reusability (modularity, reconfiguration, adaptation to new contexts). Design structured representations of workflows (processing chains, dependencies, automated calls). Develop methods for estimating the environmental impact of pipelines (energy, carbon, orders of magnitude). Compare different design and execution scenarios (reuse vs. recomputation, choice of tools or models). Contribute to the integration of these analyses within the DataGEMS platform, in coordination with other work packages. Participate in the project's deliverables and scientific publications.

Your Profil

Skills

Degree in computer science, data science, or related fields. Experience with or strong interest in data science pipelines, analytical workflows, or distributed systems. Awareness of the challenges of sustainability, efficiency, and environmental responsibility in the digital sector. Strong abstract reasoning skills, solid programming skills in C/C++ and Python, familiarity with front-end design, and collaborative skills. English is required.

Your Work Environment

DataGEMS is a HORIZON-INFRA-2024-EOSC-01-05 - HORIZON-RIA HORIZON research and innovation action whose goal is to build a fully operational and sustainable ecosystem of open-source tools for data fairness and to provide a free and open-source ecosystem of tools. These tools and a number of services cover all phases of the data lifecycle, addressing storage and management, discovery, analysis, description, publication, and reuse. The project has 12 partners across 8 European countries who will collaborate to develop new tools and services that enable faster access to FAIR-by-design datasets than ever before. They facilitate the collection and analysis of heterogeneous and/or large-scale datasets, ensure the automatic production of FAIR data at the research instrument level (e.g., weather stations), and support infrastructures with tools and techniques for metadata automation. The host team, DAISY, is a joint CNRS, Grenoble INP, and UGA research team that focuses on research issues at the intersection of AI and data management, as well as those arising from interdisciplinary fields such as education and health. The position is located in an area subject to French legislation concerning the protection of scientific and technical potential (PPST) and therefore requires, in accordance with regulations, that your arrival be authorized by the competent authority of the Ministry of Higher Education and Research (MESR).

Compensation and benefits

Compensation

Monthly gross salary between 3143,64€ and 3403,43€ according to experience

Annual leave and RTT

44 jours

Remote Working practice and compensation

Pratique et indemnisation du TT

Transport

Prise en charge à 75% du coût et forfait mobilité durable jusqu’à 300€

About the offer

About the CNRS

The CNRS is a major player in fundamental research on a global scale. The CNRS is the only French organization active in all scientific fields. Its unique position as a multi-specialist allows it to bring together different disciplines to address the most important challenges of the contemporary world, in connection with the actors of change.

CNRS

The research professions