Opportunities

Post-doc “Flexible robotics and digital twins for cardiac surgery”

Context:

This postdoctoral position is part of the RHU-ICELAND project, involving several academic, hospital, and industrial partners. The objective of the project is to develop a new transfemoral mitral valve annuloplasty solution that integrates intracardiac ultrasound imaging and robotics. This approach allows intervention on a beating heart without extracorporeal circulation, offering a mitral valve repair solution for high-risk patients who are ineligible for open-heart surgery and, in the long term, for most patients requiring mitral valve repair.

Direct annuloplasty involves affixing a ring or band directly onto the mitral annulus using anchors under echocardiographic and fluoroscopic guidance. The advantage of this technique is that it constrains the shape of the mitral annulus, closely replicating surgical mitral annuloplasty. The RHU-ICELAND project focuses on two key phases: developing a numerical model of the anatomy and the robotic system used to apply staples to the mitral valve, followed by designing and evaluating the robotic system, which is validated through numerical modelling.

Scientific Objectives:

Initially, the recruited postdoc will focus on the numerical modelling of anatomical structures (veins, heart, mitral valve, etc.). Preliminary work has already been carried out to design a numerical model of the heart and mitral valve with opening and closing cycles. The aim is to enhance this model for greater realism. The model will be used for clinician training, preoperative intervention planning, and validating the geometric, kinematic, and dynamic models of the robotic system (active catheter) during navigation from the entry point (femoral vein) to the target site (facing the mitral valve). The other medium- and long-term goal is to develop a realistic and, above all, patient-specific numerical model, meaning constructing the numerical model based on the patient’s preoperative images.

The recruited candidate will work closely with academic and clinical teams involved in the project, particularly when integrating the research into the final demonstrator. The postdoc will benefit from a stimulating research environment and access to clinical data provided by the project’s clinical and industrial partners. They will also participate in project management (meetings, decision-making, report writing, etc.).

Host Institution:

The recruited candidate will join the Institute of Intelligent Systems and Robotics (ISIR) at Sorbonne University and CNRS (Paris). ISIR is organized into several multidisciplinary teams, including RPI-Bio. Research areas include microrobotics, drones, surgical robotics, bionic prosthetics, social robots, and various intelligent and interactive systems (physical, virtual, or mixed-reality), as well as artificial intelligence. Applications address major societal challenges: health, the industry of the future, transportation, and personal services.

The RPI-Bio team (robotics, perception, and interaction for biomedical applications), to which the postdoc will be attached, conducts research in healthcare robotics on topics such as interactive systems for expert guidance (surgery), perception (visual and haptic), human-machine interfaces, telemedicine, and microrobotics. Recently labelled by Inserm, RPI-Bio has extensive experience in developing advanced robotic solutions for interventional medicine (orthopaedics, neurosurgery, ENT surgery, endovascular interventions, etc.).

Profile Sought:

– Expertise in robotics, mechatronics, simulation, and/or numerical modelling

– Advanced programming skills (C++, MATLAB, Python)

– Proficiency in a numerical simulation library for soft robots (e.g., SOFA) is a plus

– Enthusiasm for interdisciplinary research and a collaborative spirit

General information :

– Supervisors: Lingxiao Xun; Brahim Tamadazte

– Contract start date: as soon as possible

– Contract duration: 12 months, renewable for a further 12 months

– Salary: depending on experience

– Host laboratory: ISIR (Institut des Systèmes Intelligents et de Robotique), Campus Pierre et Marie Curie, 4 place Jussieu, 75005 Paris

Contact person:

Send a single PDF file containing: a CV, a cover letter, and any scientific articles you deem relevant to the application to lingxiao.xun@sorbonne-universite.fr and brahim.tamadazte@cnrs.fr. Please include ‘post-doc rhu’ in the subject line of the email.

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Post-doc : Learning in robotics, with application to grasping

Context:

During the FET Proactive DREAM project (http://dream.isir.upmc.fr/) has been defined an approach for adaptive robotics based on open-ended learning. The main goal is to allow a robot to learn without requiring a careful preparation by an expert. This approach raises many challenges, notably learning with sparse reward, representation learning (for states and actions), model learning and exploitation, transfer learning, meta-learning and generalization. These topics are considered in simulation, but also on real robotics setup, notably in the context of grasping.

Missions:

This position aims at contributing to these topics in the context of several European projects, in particular SoftManBot, Corsmal, INDEX and Learn2Grasp. Calling upon previous works in the research team, the proposed approaches need to be easy to adapt to different robotic platforms and will thus be applied to different robots (Panda arm from Franka-Emika, Baxter, PR2 or TIAGO, for instance).

Required profile:

Candidates for the position must have a PhD degree in machine learning or related field in which robotics applications (either simulated or real) have been considered.

Required skills:

An excellent background is expected in machine learning as well as an experience in robotics. Excellent programming skills in Python are expected.

General Information: 

• Position Type: Post-doctoral researcher
• Contract duration: 24 months
• Level of education required: PhD
• Remuneration : Remuneration according to experience
• Location: ISIR (Institut des Systèmes Intelligents et de Robotique), Campus Pierre et Marie Curie, 4 place Jussieu, 75005 Paris.

Contact person: 

• Stephane Doncieux
• stephane.doncieux(at)sorbonne-universite.fr
• Send your application by email, with a CV and a cover letter.

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Subject: Estimation and control of continuum robots with multiple sections

Project description

The past decade has seen the emergence of a new type of robot: continuum robots [Rus et al. 2015; Burgner-Kahrs et al. 2015; Gilbert et al. 2016; Morales Bieze et al. 2020; Childs et al. 2023; Tummers et al. 2025]. Their advantages over traditional rigid robots are numerous: a larger workspace, increased dexterity, greater compliance, the ability to navigate cluttered or tortuous environments, strong potential for miniaturization, the possibility of designing new kinematic architectures, as well as a diversification of applications, particularly in minimally invasive surgery or for handling fragile objects. The concept of continuum robots has thus enabled the emergence of a new paradigm in the field of dexterous robotics.

However, these major technological innovations still pose many challenges in terms of integration, perception, modeling, and control of these mechanisms. Consequently, many scientific issues—often fundamental—remain open before achieving effective integration of continuum robots into industrial and medical applications.

Recent advances in continuum robot control have enabled the implementation of closed-loop end-effector control strategies [Campisano et al. 2021], leading to submillimetric accuracy. However, implementing this type of control, particularly in minimally invasive surgical applications, requires robust and reliable estimation of the robot’s state.

Accurate state estimation of continuum robots is a complex problem and one of the missing building blocks for their widespread adoption. Among the various perception modalities in robotics, vision is by far the most commonly used. However, in continuum robotics, cameras are often unreliable—either due to the nature of the application, which prevents consistent visual contact with the robot (e.g., navigation in constrained environments, minimally invasive surgery), or due to self-occlusions caused by the robot’s own deformations.

This necessitates the exploration of alternative perception strategies. These generally rely on integrating additional sensors within a robotic architecture that is already highly constrained in terms of compactness. The resulting problem can then be divided into two major challenges:

– Maximizing the amount of information provided by small sensors about the robot’s state, without altering its intrinsic properties or compromising its ability to perform the intended tasks.

– Accurately estimating the robot’s state from partial or indirect measurements. This includes, for example, reconstructing the full state of the robot from position measurements at a limited number of points along its structure, or from force and torque measurements at its base. Due to the complexity of the deformations these robots undergo, these problems may be ill-posed and admit multiple solutions, particularly for the estimation of external loads.

Profile and skills required:

– Master graduation

– Knowledge in robotics, control, estimation and vision

– Skills in advanced programming

– Required level of English: Upper-intermediate. You can use the language effectively and express yourself accurately.

General information:

– Laboratory: Institute of Intelligent Systems and Robotics (ISIR), UMR 7222

– Affiliated institution: Sorbonne University

– Thesis title: Estimation and control of continuum robots with multiple sections

– Thesis supervisors: Faïz Ben Amar (Professor, Sorbonne University), Azad Artinian (Lecturer, Sorbonne University)

– Contact email: artinian@isir.upmc.fr

– Affiliation to a programme: ED SMAER

– Funding: Funding is subject to approval by the Doctoral School

Application procedure:

Candidates may apply online directly via ADUM until 18 May 2026.

To ensure a fair assessment, applications must include the documents listed below.

Documents to be included in the application:

– A detailed CV of the candidate and a cover letter explaining how their personal project aligns with that of the laboratory, on the chosen topic.

– A reference from the head of the candidate’s original Master’s programme, including ECTS credits earned, academic background, modules passed, ranking and the candidate’s average mark. As the final Master’s examination board will not have met by the application deadline, please include results from theoretical examinations and ECTS credits earned. The candidate’s ranking in the various semesters of their studies, and in particular in the first semester of the M2, are mandatory documents for a fair assessment of the candidate.

– The placement assessment form or the placement supervisor’s report

If your application is successful, you will be invited to an interview before a panel during which you will present your topic using 4 transparencies (further details will be provided at a later date).