PhD Position F/M Resilience of Telecommunication Infrastructures to Climate Change — Modeling, Impact Analysis, and Adaptation Strategies for Next-Generation Networks

PhD Position F/M Resilience of Telecommunication Infrastructures to Climate Change — Modeling, Impact Analysis, and Adaptation Strategies for Next-Generation Networks Download job offer in PDF format Contract type : Fixed-term contract Level of qualifications required : Graduate degree or equivalent Fonction : PhD Position Context Collaboration between two teams : COATI : https://team.inria.fr/coati/ - Joanna Moulierac :https://www-sop.inria.fr/members/Joanna.Moulierac/ SIGNET : https://signet.i3s.univ-cotedazur.fr/ - Guillaume Urvoy-Keller : https://webusers.i3s.unice.fr/~urvoy/ - Dino Lopez : https://webusers.i3s.unice.fr/~lopezpac/ - Clément Courageux-Sudan : https://scholar.google.com/citations?user=NukX4T0AAAAJ&hl=fr Funded by PEPR Carecloud : https://carecloud.irisa.fr/ Main activities Context and Problem Statement Telecommunication infrastructures (fixed and mobile access networks, backhaul networks) are critical components of modern socio-economic functioning. However, as highlighted by ARCEP in its note on network resilience [6], these physical infrastructures are highly exposed to the direct and indirect impacts of climate change. Extreme weather events (heatwaves, storms, floods, wildfires) as well as long-term trend shifts (rising average temperatures, sea level rise) degrade service quality, increase failure rates, and threaten to weaken isolated areas [1, 2]. While initial scientific research and exploratory studies (such as Master's thesis work based on local open data) have established empirical correlations between weather conditions and network incidents on a small scale, several major scientific roadblocks remain to generalize these approaches to a national and predictive scale: • Spatio-temporal heterogeneity and granularity of data: Crossing complex time series (weather metrics, RIPE Atlas active/passive probes, ARCEP/operator incident reports, physical network topology) requires processing noisy, incomplete, and asynchronous data. • Causality vs. Correlation: Distinguishing failures directly caused by climate factors from those resulting from cascading failures (e.g., power grid outages, traffic saturation during crises). • Prospective uncertainty: Anticipating the vulnerability of future network generations (5G standalone, 6G, fiber densification) under various IPCC climate scenarios for the 2030–2050 horizon. Scientific Objectives of the Thesis The main objective of this thesis is to build a systematic, automated, data-driven methodology to assess, predict, and enhance the resilience of telecommunication networks in the face of climate hazards. The research will focus on the following axes: 1. Data Aggregation, Coupling, and Advanced Mapping • Extending the cross-analysis between meteorological time series (Météo-France / Copernicus), incident data (ARCEP), and fixed/mobile access quality (RIPE Atlas, crowdsourced data) across the entire French territory. • Developing standardized metrics to measure the weather-climate vulnerability index of a piece of equipment or a network node. 2. Explanatory Modeling for Causality Detection • Designing statistical models capable of identifying root causes of incidents and detecting cascading failure propagation (e.g., the impact of a heatwave on cooling systems in cell sites or optical distribution frames / NROs). • Accounting for cross-dependencies with other critical infrastructures (specifically the ENEDIS/RTE power distribution network). 3. Prospective Inference and Resilience Optimization Strategies • Simulating network behavior under various future extreme climate scenarios (IPCC / Météo-France projections). • Proposing redeployment strategies, hardware hardening, or emergency dynamic routing to minimize the risk of global disconnection during extreme events. Scientific Roadblocks and Expected Contributions • Scaling and automation: Moving from a local exploratory analysis (departmental scale) to an automated data processing pipeline for high-volume streams at a national scale. • Systemic resilience: Providing a unified theoretical framework combining physical infrastructure characteristics (material exposure) with the dynamic behavior of data traffic flows. • Public and industrial decision support: Delivering a risk assessment tool that regulators (ARCEP, ANSSI) and operators (Orange, SFR, Bouygues Telecom, Free, Axione) can use to guide network hardening investments. Bibliographic References • [1] Padmanabhan, R., et al. "Residential links under the weather." Proc. of ACM SIGCOMM, 2019. • [2] Durairajan, R., Barford, C., & Barford, P. "Lights out: Climate change risk to internet infrastructure." Proc. of ANRW, 2018. • [3] Météo-France — Open data platform (meteo.data.gouv.fr). • [4] RIPE NCC — RIPE Atlas Infrastructure (atlas.ripe.net). • [5] ARCEP — Incident tracking and mobile network status (arcep-dev.github.io/siteshs/). • [6] ARCEP — Networks of the future: The resilience of electronic communications networks, Summary Note. Skills Technical skills and level required : Languages : Relational skills : Other valued appreciated : Benefits package • Subsidized meals • 75% of public transportation pass costs are reimbursed • Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.) • Possibility of working remotely (after a few months at the office) and flexible organization of working hours • Professional equipment available (videoconferencing, loan of computer equipment, etc.) • Social, cultural and sports events and activities • Access to vocational training • Social security coverage Remuneration 2300€ monthly gross salary 36-month fixed-term contract, Ph.D. student status, 2-month non-renewable probation period Apply for this position Share • Facebook • Linkedin • Twitter • Email General Information • Theme/Domain : Networks and Telecommunications Statistics (Big data) (BAP E) • Town/city : Sophia Antipolis • Inria Center : Centre Inria d'Université Côte d'Azur • Starting date : 2027-02-01 • Duration of contract : 3 years • Deadline to apply : 2026-11-22 Warning : you must enter your e-mail address in order to save your application to Inria. Applications must be submitted online on the Inria website. Processing of applications sent from other channels is not guaranteed. Instruction to apply Defence Security : This position is likely to be situated in a restricted area (ZRR), as defined in Decree No. 2011-1425 relating to the protection of national scientific and technical potential (PPST).Authorisation to enter an area is granted by the director of the unit, following a favourable Ministerial decision, as defined in the decree of 3 July 2012 relating to the PPST. An unfavourable Ministerial decision in respect of a position situated in a ZRR would result in the cancellation of the appointment. Recruitment Policy : As part of its diversity policy, all Inria positions are accessible to people with disabilities. Contacts • Inria Team : COATI • PhD Supervisor : Mouliérac Joanna / Joanna.Moulierac@inria.fr The keys to success • Master’s degree or Engineering degree in Computer Science, Data Science, or Telecommunications. • Strong skills in data analysis, machine learning / deep learning, and time series analysis. • Good understanding of telecommunication networks and Internet protocols. • Keen interest in interdisciplinary challenges (computer science, networks, climate, environment). About Inria Inria, the French national institute for research in digital science and technology, supports the French government in national research and innovation strategies in the digital field, acting as Digital Programs Agency. Inria leads over 300 research and innovation projects with its 3,500 scientists, engineers, and support staff, in partnership with universities and the digital ecosystem (businesses, entrepreneurs, and public stakeholders). Together, we explore strategic fields such as artificial intelligence, cybersecurity, quantum computing, cloud technologies, digital transformation in healthcare, digital twins, and digital technologies for defence. We develop practical solutions such as software, tech startups, partnerships with national companies, and cutting-edge training programmes. Our goal is to drive scientific, technological, and industrial excellence to ensure France’s digital sovereignty.