Context

Mobile network operators are under growing pressure to demonstrate sustainability across environmental, social, and economic dimensions while maintaining strong technical performance. In this context, the Network Design-to-Impact (NDI) paradigm proposed by the research team adopts a value-driven approach to network design, deployment and operations. Rather than optimizing only technical performance, NDI aims to maximize positive impacts such as digital inclusion, resilience, and economic viability, while limiting negative impacts such as greenhouse gas emissions, resource consumption, and e-waste across the full lifecycle.

A formal NDI methodology has also been recently proposed by the research team, structured as an iterative 8-step decision framework. It combines technical Key Performance Indicators (KPIs) assessment (coverage, capacity, throughput) with sustainability Key Value Indicators (KVIs) across environmental, social and economic pillars. It also includes sensitivity analysis to identify which network levers most strongly influence each indicator. The methodology is stakeholder-centric where KVIs are defined for actors such as operators, customers, regulators, vendors, financial institutions, and the workforce.

The next step is the practical implementation of this methodology as a software tool. This tool is intended to support analysts and strategic decision makers, managing multi-stakeholder indicators, lifecycle assessment models, network performance computation, iterative solution refinement, and trade-off visualization. It is modular and interfaces with sustainability databases and technical evaluation/dimensioning tools already in use within the entity.

The objective of this internship is to develop, implement and validate a prototype of the NDI tool by building the core computational modules defined in the NDI methodology, namely:

• Stakeholder & indicator module
• Candidate solution builder
• Evaluation scenario configurator
• Sustainability assessment engine
• Technical performance module
• Acceptability test engine
• Termination & iteration control
• Mitigation/modification assistant
• Decision support & visualization
• Sensitivity analysis module

The prototype should cover all the steps and be internally tested on at least one synthetic dataset. The development will build on the technical specification and modular architecture already defined by the research team.

This internship is suitable for a research-oriented MSc student or engineering school student (grande école, 5th year) with a background in data science, scientific computing, software engineering, or telecommunications, with a strong interest in sustainability and multi-criteria assessment.

• Strong programming skills in Python (NumPy, pandas, SciPy), experience with FastAPI or Streamlit is a plus.
• Good understanding of software architecture and modular design principles.
• Skills in versioning (Git, GitLab) is a plus
• Skills in data manipulation, data processing, data science skills is a plus.
• Basic knowledge of mobile/radio networks.
• Ability to work and interface with existing tools and databases.
• Basic knowledge of Life Cycle Assessment (LCA) methodology or capacity to learn rapidly.
• Interest in sustainability and ESG indicators.
• Fluent English (written, comprehension and spoken).
• Ability to work with an existing technical specification.
• Autonomy
• Rigor in documentation and scientific traceability

Knowledge of Brightway2, SALib, Plotly, or telecommunication networks is a plus but not mandatory if the candidate demonstrates strong technical and learning skills.

Au sein d'INNOVATION, vous serez intégré(e) dans une équipe de recherche à la pointe de l'innovation et de l'expertise sur les réseaux mobiles du futur (5G/6G, virtualisation, mobile edge computing, AI & networks...). Vous ferez partie d'un écosystème de recherche côtoyant des experts pluridisciplinaires en créant la nouvelle génération des réseaux mobiles soucieuses de l'impact sur l'environnement, permettant la mise en œuvre concrète des concepts étudiées, bénéficiant de plateformes de simulations (5G+) ».