Opportunities

Job title: Machine learning for human-robot collaboration

Context and objectives :

This position focuses on developing machine learning techniques to enhance human awareness in human-robot interaction by integrating situation assessment and action planning. The successful candidate will contribute to cutting-edge research at the intersection of robotics, artificial intelligence, and human interaction, with an emphasis on designing and evaluating robotic systems that facilitate seamless collaboration with humans.

The position is for 18 months contract, but there is a possibility to be extended depending on the performance and circumstances. The position is open at both the engineer and post-doctoral levels for candidates with a strong background in machine learning, human-machine interaction, or robotics.

Responsibilities:

– Develop advanced situation assessment techniques using machine learning to accurately represent user preferences, behaviors, and characteristics based multimodal data to efficiently plan actions.

– Collaborate with interdisciplinary teams including computer scientists, humanities, and designers to ensure the usability and effectiveness of developed techniques.

– Publish research findings in top-tier conferences and journals in the field of Human-Machine Interaction and Machine Learning (mainly at the post-doc level)

Requirements :

The successful candidate should have:

– Experience in human-machine interaction

– Good knowledge of Machine Learning Techniques

– Good knowledge of experimental design and statistics

– Excellent publication record

– Strong skills in Python

– Willing to work in multi-disciplinary and international teams

– Good communication skills

Additional information:

– Contract start date: as soon as possible

– Contract duration: 18 months

– Quota of work : 100%

– Level of education required: Master’s degree / Engineering school – Doctorate

– Salary: depending on experience

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

Application :

Interested candidates should submit the following by email in a single PDF file to: mohamed.chetouani[@]sorbonne-universite.fr with the subject: Application ML for Human-Robot Collaboration

– Curriculum vitae with 2 references (recommendation letters are also welcome)

– One-page summary of research background and interests

– At least three papers (either published, accepted for publication, or pre-prints) demonstrating expertise in one or more of the areas mentioned above

– Doctoral dissertation abstract and the expected date of graduation for a post-doc position levale (for those who are currently pursuing a Ph.D)

Application’s deadline: April 21, 2025.

Download this job offer

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.

Download this job offer

Job title: Post-doc on haptic and multisensory human-computer interactions

Context:

This post-doc is part of the NeuroHCI ANR project. The overall goal of NeuroHCI is to improve human decision making in the physical and digital worlds in interac,ve contexts. There are various scenarios in which a human makes a decision with an interac,ve system. The decision might be about a complex real-world choice assisted by a computer (e.g. medical treatment), the choice of a method to achieve a digital task (e.g. editng a photo with the preferred tool), or the way we decide the best way to perform a haptic interaction.

Missions:

The envisioned scientific approach will rely on optimizing the haptic feedback delivered to the user with relation to vision and hearing by leveraging computational models of multisensory integration. Thus, the scientific activities of the project will revolve around questions including but not limited to:

– How to ensure that the inconsistencies between what the user sees and what the user feels does not break the illusion and how to mitigate their effects on user experience?

– How visuo-haptic inconsistencies influence users’ strategies (e.g. which objects they will decide to interact with) and high-level decision making?

Required profile:

The ideal candidate must have a PhD degree and a strong background in human-computer interaction and/or cognitive science.

Required skills:

– Experience in haptics is a strong plus ;

– Strong skills in Python, Matlab or equivalent ;

– Good knowledge of experimental design, psychophysics and statistics ;

– Excellent publication record ;

– Willingness to work in a multi-disciplinary team ;

– Good communication skills.

General Information:

• Contract start date: at the latest 06/01/2024
• Contract duration: 24 months
• Working time: 100%
• Desired experience: beginner at 4 years old
• Level of studies required: PhD
• Host laboratory: ISIR (Institut des Systèmes Intelligents et de Robotique), Campus Pierre et Marie Curie, 4 place Jussieu, 75005 Paris.

How to apply:

– David Gueorguiev ; david.gueorguiev(at)sorbonne-universite.fr

– Send your application by email, with [name of offer] in the subject line, a CV and a cover letter.

Download this offer

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.

Download this offer

Doctoral, Postdoctoral or research engineer positions for the HCI Sorbonne group (Human Computer Interaction)

Context:

We have multiple postdoctoral and engineering positions in the HCI group (https://hci.isir.upmc.fr) at Sorbonne Université, Paris, France.

Missions:

We are searching for curious minds who want to conduct cutting-edge research at the intersection of HCI with VR, Haptics, Robotics or AI. Possible topics/areas of research are:

• Novel Interaction techniques in VR,
• VR and haptics for gaming or training,
• Computational models for learning, decision making and human performance,
• AI-based recommendation systems.

Some of our previous work in these areas:

• CoVR (UIST21): https://dl.acm.org/doi/10.1145/3379337.3415891
• AI-based Recommendation systems (CSCW 21): https://dl.acm.org/doi/abs/10.1145/3476068?sid=SCITRUS
• Adapting UIs with Reinforcement Learning (CHI 21): https://dl.acm.org/doi/abs/10.1145/3411764.3445497
• Mixed Control of Robotic systems (CHI 20): https://dl.acm.org/doi/10.1145/3313831.3376795

Required profile:

For the postdoctoral position, a Phd degree in Computer science, HCI or other field related to our research areas is required.

Required skills:

• strong programming and analytical skills,
• strong background in at least one of the following areas (HCI, VR, Haptics, Robotics, AI).

More information : 

• Type of position: Postdoctoral or Research Engineer position
• Start date: as soon as possible
• Duration: 1 to 2 years
• Level of study required: Master 2 (for engineer), PhD (for post-doc)
• Location: ISIR (Institut des Systèmes Intelligents et de Robotique), Campus Pierre et Marie Curie, 4 place Jussieu, 75005 Paris.

Contacts: 

• Gilles Bailly et Sinan Haliyo
• Email : gilles.bailly(at)sorbonne-universite.fr ; sinan.haliyo(at)sorbonne-universite.fr
• Application: Send your application by email, with a CV and a cover letter.
• Application deadline: None

Download the offer

Thesis topic: Generation of 3D models of anatomical structures by deep learning from 2D images

Context:

The number of spinal surgery operations is rising steadily, both for trauma-related cases and for degenerative pathologies. In the latter case, the increase can be explained by the ageing of the population and possibly by changes in lifestyle, such as an increase in sedentary lifestyles and obesity. In addition to this increase in the number of cases of spinal degeneration, there has also been an increase in diagnostic capabilities, new treatment modalities and a broadening of clinical indications. As an example, around 450,000 arthrodeses were performed in 2014 in the United States alone, an increase of 118% since 1998. Lumbar fusions alone accounted for around 200,000 operations in the United States in 2015, 62% more than in 2004, at a cost of several tens of thousands of dollars per operation and a total annual cost of several billion dollars. Worldwide, several million pedicle screws are used in spinal surgery every year.

Scoliosis is treated surgically. It involves inserting screws into the vertebral pedicles to stabilise the spine. These screws are connected by rods to correct the abnormal curvature in three dimensions. This technique ensures rigid fixation, promoting vertebral fusion and improving functional and aesthetic results. The placement of these screws is complex and difficult, particularly in certain patients. The literature reports that, on average, without a support system, around 24% of pedicle screws are incorrectly positioned, ultimately leading to potentially serious neurological symptoms.

In parallel with an increase in the volume of pedicle screws placed, the field of computer-assisted surgery has seen a major boom, with the development of three-dimensional navigation solutions, the use of robotics and augmented/mixed reality methods. Each of these solutions has its own advantages and disadvantages. For example, navigation systems make pedicle screw placement more accessible to junior surgeons and reduce certain risks and complications. However, they are expensive, can extend the duration of surgical procedures, and are less accurate when not used optimally. Robotics and augmented/mixed reality provide added clinical value, particularly in the phase of inserting screws into the pedicles, given that the insertion trajectories are known.

Scientific objectives:

In a recent collaboration between Sorbonne University, Trousseau Hospital and the company SpineGuard, we removed several scientific barriers to the safe insertion of pedicle screws. In particular, we have developed a functional robotic platform for spinal surgery and real-time breach detection methods enabling us to stop the screw insertion task before a breach is created in the spinal canal. However, the approaches developed to date assume that the 3D trajectory of screw insertion into the pedicle is known precisely in the real world.

The aim of this doctoral project is precisely to address the problem of estimating the 3D trajectory of screw insertion during surgery. Currently, trajectories are planned by the surgeon on the basis of pre-operative imaging (e.g. CT scan). These trajectories are then transposed onto the patient on the day of the operation, assuming that the pre-operative 3D model corresponds exactly to what the surgeon sees.

In addition, the surgical procedure itself induces deformations in real time, which compromise the registration and planning of trajectories. In order to improve this registration and therefore the accuracy of the surgical procedure, we would like to explore the use of a conventional non-irradiating 2D visual sensor (e.g. RGB camera) to access the upper (visible) part of the spine in real time during the operation. In other words, this means observing the spinous processes and the transverse processes. The scientific challenge we propose to explore is to reconstruct each vertebra in 3D using 2D visual information from RGB images using deep learning methods. This relatively recent discipline has received growing interest from the computer vision community, significantly advancing the state of the art. Until recently, the reconstruction of a 3D model required several 2D views of the object/scene or, at the very least, a large database of annotated 2D image – 3D model (e.g. CAD) pairs, which severely limited its deployment in disciplines such as surgery due to the lack of annotated data.

To meet the scientific challenges and clinical needs, several avenues of work are envisaged. The first involves generating synthetic 2D images from 3D models, followed by domain adaptation so as to benefit from self-supervised learning of the 2D/3D transformation. This method, proposed for rigid objects, could be extended to non-rigid objects using displacement vector fields. Another promising approach is the result of recent work enabling a 3D model to be reconstructed from a simple 2D view. The tools used by these methods, and in particular triplanes, could be used for our application, by deploying them locally for each vertebra. A graph-based scene context network could then refine the initial 3D pose of each vertebra and their relative arrangement.

We already have a database of segmented and annotated vertebrae from patient scans, which we are continually adding to. As a result, the prediction of the 3D shape of vertebrae from 2D images can be enriched by the 3D information from the scans.

Support team:

It will consist of Brahim Tamadazte (DR CNRS, ISIR, SU), Catherine Achard (PU, ISIR, SU) and Raphaël Vialle (PUPH, APHP, Hôpital Trousseau, SU). Collaboration between ISIR and Hôpital Trousseau is well established, notably through participation in the EU H2020 FAROS project, the FHU SpineMed2 project, and the ANR RODEO project, resulting in several co-supervision of theses (3) and trainee doctors (2). These collaborations have enabled us to structure a significant research activity around the use of robotics, computer vision and AI to improve spinal surgery protocols.

In this type of arrangement between ISIR and a hospital centre, we usually involve one or more interns who come to do 6 to 12 month Masters placements. This enables greater interaction between the medical world and academic research. This model has amply demonstrated its translational capacity, leading to the creation of several companies (Basecamp Vascular, MovaLife) or the marketing of medical devices via specialist companies (Endocontrol, Koelis, GEMA, Moon Surgical, GE Healthcare, Robeauté and SpinGuard).

Application:

There are two funding possibilities (IUIS and ED SMAER) for this thesis project. Double applications are therefore required (deadline 5 May 2025):

– ED SMAER: https://adum.fr/as/ed/voirproposition.pl?langue=&site=edsmaer&matricule_prop=62877

– IUIS: https://lime3-app3.sorbonne-universite.fr/index.php/283197?lang=fr

Contacts :

– Catherine Achard, PU Sorbonne University (ISIR): catherine.achard@sorbonne-universite.fr

– Brahim Tamadazte, DR CNRS (ISIR): brahim.tamadazte@cnrs.fr

Download this thesis offer

Internship topic: Design of a virtual environment coupled with a haptic system for dental training.

Context and host laboratory :

As part of a collaboration between the Institut des Systèmes Intelligents et de Robotique (ISIR: https://www.isir.upmc.fr) and a young innovative company in training and dental surgery (Augmenteeth: https://augmenteeth.com/), we aim to transform the practice of dental implantology by integrating cutting-edge technologies to improve the precision, safety and efficiency of surgical management. This will inevitably involve the training of dental surgery students by providing technological training solutions that complement or break with current practices, as other surgical disciplines have done in recent years.

The trainee will join the Institute of Intelligent Systems and Robotics (ISIR) at Sorbonne University and the CNRS (Paris). ISIR is organised into several multidisciplinary teams, including RPI-Bio. Research activities include microrobotics, drones, surgical robotics, bionic prostheses, social robots and all kinds of intelligent and interactive systems, whether physical, virtual or mixed reality, artificial intelligence and so on. Their applications address major societal challenges in healthcare, the industry of the future, transport and personal services.

The RPI-Bio team (Robotics, Perception and Interaction for Biomedicine), to which the trainee will be attached, is conducting research into robotics for healthcare on the theme of interactive systems to assist expert gestures (surgery), perception (visual and haptic), human-machine interfaces, telemedicine and microrobotics. RPI-Bio, which recently received the Inserm label, has extensive experience in developing advanced robotic solutions for interventional medicine (orthopaedics, neurosurgery, ENT surgery, endovascular surgery, etc.).

Aims of the placement:

Initially, the trainee will be asked to study the learning and training needs of dental surgery students, in particular through questionnaires carried out with dental surgeons. This study will be supplemented by bibliographical research and technological monitoring relating to dental training.

The second stage will involve the implementation of the training environment, which is divided into two essential stages:

– First stage: The first stage will involve setting up a virtual environment (digital twin) consisting of a digital model of a patient (head and torso) and the upper and lower dental arches. These digital models will be acquired commercially, then modified and adapted to allow jaw opening and closing movements. A digital model of a typical dental drill will be added to the virtual environment.

– Second stage: The second stage will be devoted to coupling the digital twin with a haptic feedback robotic arm of the Haption type (https://www.haption.com/), which will be equipped with a dummy dental drill. This will be followed by the development and implementation of control laws (position, impedance) for the haptic arm. The clinical objective is to restore milling forces to the dental surgeon via the haptic arm. The control strategies will be evaluated in the context of the surgical procedure (milling, extraction or other).

Profile required :

– Robotics/automatics, digital modelling and virtual reality

– Advanced programming skills (C++, Python), ROS2

– Knowledge of 3D design tools (Blender, SolidWorks or equivalent)

– Strong interest in interdisciplinary research and a spirit of collaboration

Additional information:

– Supervisors : Philippe Gauthier, Aline Boudry, Samuel Hadjes and Brahim Tamadazte

– Starting date: May / June 2025

– Length of placement: 6 months

– Level of studies required: Master 2 / Engineer

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

Contact person:

– Aline Boudry: aline.baudry@isir.upmc.fr

– Brahim Tamadazte: brahim.tamadazte@cnrs.fr

– How to apply: send your application by email, with [Internship] in the subject line, a CV, a covering letter and M1 and M2 transcripts (or equivalent).