Vacancies at FEMTO-ST

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MECANIQUE: "Contributions to the design of metacomposites for structural control"

Context : Adaptive materials are materials with additional properties compared to conventional materials (sensing or actuation in this project with the use of piezoelectric materials). They can thus act directly on their environment and improve the overall properties of the structure in which they are integrated (durability, efficiency, instant response to environmental stimuli). Composites are key materials in many fields (transport, aeronautics, renewable energies, etc.). They meet the need to lighten parts while retaining excellent mechanical properties. The combination of these two technologies has led to the emergence of "super" materials with controllable structural properties: adaptive meta-composites. Adaptive meta-composites feature new, customized properties, developed according to functional specifications.

The proposed PhD work focuses mainly on WP1, with research actions aimed at deploying physics-based numerical intelligence in a systems approach to develop decision support tools for the robust design of adaptive meta-composites taking advantage of multi-scale multiphysics simulations and control strategies.

This PhD is open at FEMTO-ST (Besançon-FR), in close collaboration with LTDS (Ecully), funded by ANR project ASTRIA, with partners SYMME (Chambéry), ICB (Belfort), ROBERVAL (Compiègne), LDTS (Ecully) and FEMTO-ST (Besançon).


OPTICS :" Nanofiber sensors for hard radiative environment"

Context : High‐orbit satellites allow for coverage of a large area on Earth. However, these satellites are subjected to significant radiative disturbances that greatly reduce their lifetime. The technology we propose involves replacing the metallic filament of a Pirani gauge (a vacuum pressure sensor) with a thinned optical fiber. We have observed that when light from a laser propagates through the optical fiber, a portion of it is absorbed by the material, causing an increase in the temperature of the fiber through convection.

Applicant profile : We are looking for a student with knowledge in the field of photonics, signal processing, and an interest in optical fiber sensors for this thesis. Skills in thermodynamics and materials chemistry will be advantageous.



DISC : "Adaptation of component-based hierarchical systems: Application to modular robots"

Context : The overall objective of our work is to model and control (self-)adaptive systems. More specifically, we consider systems composed of a multitude of components, small in size and similar in nature, that collaborate for a common global goal, as for example in the context of the Internet-of-Things (IoT). Modular robots (https://projects.femto-st.fr/programmable-matter/) are an example of such systems [1,2,8]. The structure of such systems is heterogeneous. Our modeling of such systems and the programming of elements/blocks must be based on measurements depending on structures/patterns and power points, in order to allow subsequent optimization of physical aspects such as, for example, energy consumption, and computer aspects such as, for example, memory space and number of messages exchanged.

Applicant profile : The proposed subject links theory (models: automata and finite state machines) and practice in the application domain (modular robots). It requires an interest in instrumentation of programmable robotic systems. Some knowledge of their programming will be appreciated.

Application deadline : before May 19th 2023


 PhD Supervisor : Olga Kouchnarenko - olga.kouchnarenko@femto-st.fr

Co-PhD supervisor : Frédéric Lassabe - frederic.lassabe@femto-st.fr

+ d'infos :
PDF icon kouchnarenkolassabe_sujet_contrat_doctoral_2023.pdf

MN2S :" Development of an instrumented physiological microdevice"

The doctorate project is aiming at modelling the vascularization of the human brain in a tumor context by developing a microdevice that mimics blood flow. It will involve the development and characterization of microchips.

Solid scientific bases in biomaterials and engineering sciences are required


MECANICS : "Study and modeling of the impact of hydrogen gas on the constituent materials of the hyperbaric storage tank"

Job Description : The Applied Mechanics Department of the FEMTO ST Institute, has been involved in the hydrogen storage theme for 20 years, on issues related to mechanics and materials science. The recruitment aims at reinforcing the human resources for the HYperStock project. The HYperStock project is one of the 7 targeted projects of the PEPR - Decarbonized Hydrogen (France 2030) which aims to consolidate the French scientific leadership in the field of storage and distribution of hydrogen under high pressure. Reducing the carbon impact of compressed hydrogen transport and storage solutions requires action on the materials used, by integrating the way they are obtained, the transformation processes, and their recyclability. This project aims to establish a "materials in a severe H2 environment" reference system, coupled with selection methodologies, and is divided into two main families of materials

  • Non-metallic materials (elastomers, thermosets, thermoplastics and composites)
  • Metallic materials (steels, aluminum alloys...

Profile : The candidate must have a Master's degree in mechanics or materials science and a proven taste for experimentation as well as knowledge of modeling. Specific skills in polymeric materials will be appreciated. Rigor, autonomy, teamwork and good communication skills (written and oral) in French and English are expected from the candidate. A strong sensitivity to sustainable development and life cycle analysis will be particularly appreciated and valued.


OPTICS : "Novel spin-orbital optical state in plasmonic nanostructures"

Context: This doctoral thesis, funded by the French Ministry of Research (MESRI grant), addresses the field of nano-optics. The research project will be conducted in the Optics department of FEMTO-ST (Nano-optics team), in collaboration with the "Micro Nano Sciences and System" department and the MIMENTO platform of the Institute.

Objective: This thesis aims to demonstrate a new state of the light field resulting from the transposition to optics of a concept of chiral structure of magnetization existing in magnetic materials. Chiral magnetic modes being nowadays widely studied for robust information processing, their transposition to optics opens new prospects in numerous application domains, including classical and quantum information processing.



Automatic Control : "Uncertainty quantification for machine and deep learning techniques"

Job context and motivation : Most of the real physical system and everyday situations include uncertainty. This is the case for medical diagnosis, weather forecasting, evolution of the stock market and so on. In the literature two types of uncertainty are distinguished: aleatoric uncertainty denotes the one that is inherent to the data, e.g., noise in measurements or natural variability of the inputs, and epistemic uncertainty related to the model and due to lack of knowledge. Measuring the uncertainty is important, so as to support the user in the action to take. For example, when an anomaly is detected, with weak confidence level, another source of information should be added (image, human intervention, etc.) before planning intervention actions. More generally, quantification of the prediction uncertainty allows to trust or not predictions. In fact, incorrect overconfident predictions can be harmful and lead to erroneous decision.

Applicant profile: Master in applied mathematics (or equivalent). Probability, statistic. Good skills in Python programming. Experience in machine learning/deep learning
Financing Institution: MESRI
Application deadline: 15 June 2023
Start of contract : Fall 2023

How to apply: Please send a motivation letter, a detailed CV and transcript of results to the above email addresses


Noura Dridi (noura.dridi@ens2m.fr),

Zeina Al Masry (zeina.al.masry@ens2m.fr),

Noureddine Zerhouni (zer- houni@ens2m.fr)

+ d'infos :
PDF icon thesisofferfemto.pdf

ENERGY : "Multi-physical Model of Lithium Battery including Aging based on Experimental Results"

Context : The PhD position is part of the Horizon Europe project ENERGETICS and is funded for a duration of 36 months.

Scientific Objectives : The focus of the Ph.D. thesis is on the development of a multi-physical model of a lithium battery, based on measurement results that have to be generated by the Ph.D. student in our laboratory:

Review of the related state-of-the-art,
Collection of existing approaches for accelerated ageing tests,
Definition and conduction of accelerated ageing tests,
Development of multi-physical model allowing to predict the battery behavior and aging in
different conditions of battery life based on literature results and experimental results (digital twin),
Cooperation in elaboration of battery management system and test on the digital twin,
Contribution to experimental validation,
Writing of the thesis document and defense.

Expected qualifications : Master’s or 5-year engineering degree in electrical engineering, renewable energies, or a related field, Interest for energy storage topics and research,
Basic knowledge in electromobility and lithium-ion batteries,
Experience with Python and/or Matlab programming,
Good level of written and oral English,
A good level of French is a plus.



ENERGIE : PhD "Digital Twin for Ageing Resilient Control of Hydrogen-Based Microgrids"

Context :
Reducing greenhouse gas emissions is a challenge for our planet. We must recourse to the installation of sources of renewable origin, decentralized by nature. The project aims to develop an aging resistant control for a microgrid including different sources and charges in link with energy storage. The Ph.D. position is part of the ANR project Genial (Gestion d’éNergie d’un mIcro-réseAu à hydrogène résiLient au vieillissement- Stabilisation, résilience, optimisation sur cycle de vie). It is funded for a duration of 42 months.

Expected qualifications
• Master’s or 5-year engineering degree in electrical engineering, applied mathematics or a
related field,
• Interest for energy issues and research,
• Knowledge in power systems, renewable energy, hydrogen energy, optimization, 
• Experience with Python and/or Matlab programming,
• Good level of written and oral English,
• A good level of French is a plus.

Additional Information
Location: FEMTO-ST at Belfort, France
Dates: october 2023 to september 2026
Financial support: ANR-22-CE05-0026, GENIAL project, https://anr.fr/Projet-ANR-22-CE05-0026
Approximate gross salary: 2044 €/month