Context : Unlike for new on-road light-duty vehicles, for which mandatory carbon dioxide (CO2) emissions standards have been in place in the European Union (EU) for a decade, the CO2 emissions standards for new on-road Heavy-Duty Vehicles (HDV) were only adopted in 2019. This delay is particularly due to more stringent requirements, to substitute the diesel engine-based HDV, in terms of lifetime, driving range or refueling time. Today, a fast deployment of new types of on-road HDV to reduce the ecological footprint of transportation is then required. To tackle this, the EU aims to deploy zero- emission vehicles using battery or hydrogen fuel cell

Objectives : The PhD thesis aims to develop a generic method to scale single-stack fuel cell and multi-stack fuel cell system. The scaling laws will be developed for relevant properties, such as losses, as well as component parameters, by taking into account different active surface areas. This will be done by using Energetic Macroscopic Representation (EMR) formalism to develop innovative laws that allow to up- or down-size reference components, making it needless to redo time consuming design step [...]

Environment : The L2EP (Laboratory of Electrical Engineering and Power Electronics, ULR 2697, https://l2ep.univ-lille.fr/en/) has about 100 researchers, including 36 Professors and 42 PhD students, in the field of innovative electrical systems. Its control team is internationally recognized for the energy management of various electrified vehicles. Since 1990, the control team of L2EP has developed various generic method, such as the EMR graphical formalism. EMR is nowadays internationally taught and annual EMR summer school is organized every year (www.emrwebsite.org). A scientific platform of 150 m2 is dedicated to validate new electrified vehicle concepts, from subsystems to vehicles, for more efficient and less pollutant transportation systems (https://ev-platform.univ-lille.fr/). The FEMTO-ST (Franche-Comté Electronics Mechanics Thermal Science and Optics – Sciences and Technologies) institute (CNRS UMR 6174, https://www.femto-st.fr/en) is a joint research laboratory whose competences cover several fields of engineering sciences with 7 departments, including the Energy department. With 130 members, the Energy department is very involved in Hydrogen Energy to design, evaluate, develop and integrate systems based on the use of the hydrogen energy vector for stationary and on-board applications, while taking account human and social sciences

Contact: 

walter.lhomme@univ-lille.fr ; elodie.pahon@utbm.fr; samir.jemei@univ-fcomte.fr

 

+ d'infos :

offre_these_femto-l2ep.pdf

Description  : Physics-Informed Neural Networks (PINNs) have emerged as a paradigm for solving forward and inverse problems in computational mechanics by integrating physical laws directly into the learning process. Recently reintroduced by Raissi et al. (2019), PINNs enforce governing equations, typically partial differential equations (PDEs), as constraints in the neural network loss function, enabling the use of sparse or indirect data to infer system behavior.[...]

This PhD studentship is fully funded for 3 years, from October 2025 to September 2028.
Language: French or English only
Location: FEMTO-ST Department of Applied Mechanics, SUPMICROTECH, Université Marie et Louis Pasteur, Besançon (FR)
Deadline for application: June 15, 2025

Contact: 

morvan.ouisse@femto-st.fr

+ d'infos :

2025_pinn_phd.pdf

Context : After the numerical revolution that was triggered by generative AI which was based on Large Language Models (LLMs) [1] and initiated by OpenAI and its ChatGPT chatbot, AI agents [2] are expected to be the next big technology in AI and it was the top trending technology in 2024 according to Gartner. AI agents are also based on LLMs but have more capabilities such as decision-making, problem-solving, interacting with external environments and executing actions. Contrary to LLMs, AI agents’ response is not limited by the data used to train them. To answer complex requests to which they do not have the full knowledge base, AI agents can perform task decomposition and create a workflow of specific subtasks. These subtasks might be solved using external tools that the AI agent can call. These tools can include external datasets, web searches, APIs, specialized AI models and
even other AI agents. After each subtask, the agent can update its knowledgebase, reassess its plan of action and modify it if necessary. Moreover, AI agents can improve their reasoning and accuracy
by learning from the feedback returned by other AI agents and humans. This will allow them to better
align their results with the users’ intended goals and avoid repeating the same mistakes by storing
solutions to previous obstacles in a knowledge base..[...]

As a case study, the proposed approaches in this PhD thesis will be applied to the pre-authorization in healthcare insurance. It represents a significant administrative burden for healthcare providers, resulting in delays in patientcare, increased operational costs, and clinician burnout. Healthcare insurance pre-authorization processes suffer from several critical issues:
• Time-consuming manual review of patient records and insurance policies, creating significant bottlenecks.
• Inconsistent interpretation of coverage criteria across reviewers, leading to systemic issues requiring internal reforms and enhanced training programs.
• High error rates in clinical documentation and coding, which automated systems like InsightRT have shown promise in reducing by integrating with electronic medical records [3].
• Delays in patient care due to administrative processing time, with orthopedic practices seeing mean approval times extending over 30 days for procedures like total hip and knee arthroplasties [4].
These challenges result in approximately$31 billion in annual administrative waste in the US healthcare system alone (American Medical Association, 2023), with 92% of physicians reporting that preauthorization processes negatively impact patient clinical outcomes.

Application deadline : 12/05/2025
Start date : 01/10/2025
Gross Salary : 2200€

Contact: 

raphael.couturier@univ-fcomte.fr

jean-claude.charr@univ-fcomte.fr

+ d'infos :

sujet_de_these.pdf

The thesis will be housed in the Applied Mechanics Department (~110 people including ~50 teacher-researchers, researchers and technicians). The Mat'éco team is structured around two areas of application: bio-based composite materials and hydrogen storage. It has around ten PhD and Masters students working on multiscale and multimodal experimental techniques and numerical simulations using finite elements or discrete elements, with the aim of considering thermo-mechanical couplings as well as chemical, hydrous or gaseous couplings.

Context :
The relevance of hydrogen as an energy carrier and its role in the ecological transition are well established. Safe, energy-efficient storage solutions are the sine qua non of its green credentials. A long-term storage solution will need to be able to reinvest green hydrogen from electrolysis during peaks in consumption, thanks to the overproduction of electricity from renewable sources (wind, hydro, solar, etc.) during periods of under-consumption. The solid storage of H2 by reversible hydriding of intermetallic alloys, usually in powder form, is a promising technology because it is safe, requires no heavy infrastructure and offers excellent energy efficiency, since it is produced at low pressure (from 1 to 10 bars: little compression, fewer leaks) and at near-ambient temperatures (between 10 and 80°C).

DESCRIPTION OF CYCLAHMID PROJECT (CYCLage des Alliages Hydrurés : MIcrostructure et Décrépitation) :
This thesis is part of a Graduate School EUR EIPHI project, with support from the Bourgogne-Franche Comté region. The CYCLAHMID project explores the problem of the microstructure - storage - decay link through the comparative study of two intermetallics and an HEA. In this project, you will benefit from the combination of DMA/FEMTO ST's expertise in multi-scale mechanical characterisation and working under hydrogen and PMDM/ICB's expertise in structural and microstructural characterisation of high-reactivity materials.

PROFILE REQUIREMENTS :
Master student in Mechanical Engineering or Materials Sciences, final year of engineering school or already graduated.
• Knowledge in mechanics of metallic materials, including production processes, characterization and mechanical and microstructural modelling, are expected. An interest in experimentation, materials characterization and the development of new experimental techniques would be an advantage. Knowledge of solid phase change materials or in hydrogen as an energy carrier frame would be appreciated, but is not essential.
• Most of all, we are looking for candidates who are rigorous, methodical and committed.
• Fluency in written and spoken English is essential for scientific communication (articles, international conferences).

Starting date : 2025 September / October

Contact: 

anne.maynadier@univ-fcomte.fr
david.chapelle@univ-fcomte.fr

+ d'infos :

offre_these_cyclahmid_sr.pdf