Doctorant

Publications connexes (en libre accès)

• (AC+21) Julien Alexandre dit Sandretto, Alexandre Chapoutot, Christophe Garion, Xavier Thirioux, and Ghiles Ziat. Constraint-based verification of formation control. In CDC, pp. 7136–7141. IEEE, 2021.
• (GH25) Gleirscher, M., Hönnecke, P. (2025). A Parametric Model for Near-Optimal Online Synthesis with Robust Reach-Avoid Guarantees. In: Bridging the Gap Between AI and Reality. AISoLA 2024. LNCS, vol 16032. Springer.
• (M24) Merlinge, N. (2024). Set inversion and box contraction on Lie groups using interval analysis. Automatica , 165 , .

Contexte

ENSTA is an institution of higher education and research under the supervision of the Ministry of the Armed Forces. The school trains civil, military, and defense engineers, as well as highly qualified cadres for the public and private sectors, particularly in the fields of defense, security, transportation, energy, maritime activities, digital technologies, and high‑technology. ENSTA contributes to the transformation of national strategic sectors by integrating research, innovation and training. It is part of the Institut Polytechnique de Paris and actively participates in interdisciplinary research centers, including CIEDS and the newly created Centre interdisciplinaire Mers & Océans.

Projet de Thèse: “Robust Estimation & Control of Aerial Co‑Manipulators”

Laboratoires : U2IS & ONERA Paris‑SaclayResponsables : Mario Gleirscher & Julien Alexandre dit Sandretto, ENSTA Paris‑Saclay ; Nicolas Merlinge, ONERA Paris‑SaclayÉcole doctorale : Institut Polytechnique de Paris (IP Paris)Bourse : CIEDS 2026 « RoCAM » financée par l’AID.

Contexte et motivation

The robust control of a set of aerial robots jointly manipulating non‑rigid loads is an extraordinarily complex problem, especially when dealing with partial observability, imprecise state estimators, control disturbances, noisy communications, and various other perturbations.

Objectif de la recherche

The RoCAM project aims to develop an adaptive estimation technique and optimal control for multi‑AAV systems transporting non‑rigid loads, surpassing state‑of‑the‑art approaches while guaranteeing precise control.

Approche et procédure envisagée

The project builds on recent advances in robust estimation and optimal control. Robustness is enhanced by accounting for uncertainties such as imprecise state estimation and wind disturbances. Real‑time capability will be achieved via adaptive approximations. Key research challenges include: (i) handling nonlinearities in estimation and control models; (ii) compensating ambiguities in unobservable variables; (iii) generating sufficiently accurate predictions for decision‑making; and (iv) deploying efficient estimation and control techniques capable of real‑time operation.

Caractéristiques d’un bon résultat

The estimation and control models must be accurate; the algorithms should match or surpass state‑of‑the‑art performance; and they should be suitable for online deployment in a laboratory demonstrator.

Niveau de diplôme et formations

Master or engineering degree.

Emploi

Contract of 3 years (CDD).Start date: November 2026.Location: ENSTA Campus Paris‑Saclay, 828 boulevard des Maréchaux 91762 Palaiseau – Cedex. The site is accessible by car (parking for staff) and public transport.Full‑time position (25 annual leave days, 18 RTT annual).

Avantages

• Employer contribution to transport (75 % of cost)
• Durable mobility package (up to €300 / yr)
• Possibility of teleworking (subject to manager approval and request)
• Employer subsidy for the administrative restaurant and/or cafeteria
• Social action committee with events, sports facilities, and a childcare centre for staff children aged 6‑plus with discounted rates (Paris‑Saclay campus)
• Health insurance (50 % employer contribution)

Aménagement du poste de travail et recrutement inclusif

All positions are open to candidates with disabilities. ENSTA promotes recruitment that favors equality, diversity, and inclusion. All applications are considered without distinction of age, disability, sex, nationality, religion, or sexual orientation.

Modalités de candidature

Final year students may apply before the official award of their degree. Complete application to be downloaded and submitted, including:

• Motivation letter (maximum 1 page)
• Updated CV (maximum 2 pages)
• Transcript excerpts for the last two academic years, ideally including courses related to the topic
• Sample of scientific work related to the position (e.g., master thesis if sole author, or seminar presentations if first author), if available
• Up to three university references (full name, role, and institutional email)
• One or more letters of recommendation, if available

Applications from candidates without French nationality will undergo additional verification by the competent authorities. Shortlisted candidates will be invited to a 10‑ to 15‑minute presentation and discussion of a scientific article, followed by an interview. Applications will be processed until 31 July or until the position is filled.

Pré‑requis du poste

• University or engineering degree in applied mathematics (statistical and numerical methods), control theory (robotics), electrical engineering (signal processing, mechatronics), or computer science (digital control).
• Master’s level knowledge in at least one of the following areas: robust estimation, predictive control, digital control.
• Interest in the control of autonomous robots and multi‑agent systems in the domain of aerial logistics and transport.
• Proficiency in programming languages C, C++ and Python, including libraries related to the above themes.
• Interest in scientific writing and publishing; commitment to proactive engagement and to achieving the highest scientific standards.
• Ability to work reliably within agreed deadlines and to integrate and communicate with the surrounding research team.
• English proficiency (written and spoken, C1 level if possible). French knowledge (B1 or higher) is desirable.

Égalité d’Opportunités

ENSTA is committed to recruiting in a manner that promotes equality, diversity, and inclusion. All candidates are considered without any distinction based on age, disability, sex, nationality, religion, or sexual orientation.