PhD thesis offer: An agent-based digital twin for the simulation and the event prediction in th[...]

Université Marie et Louis Pasteur; France; Sur place; EUR 35 000 - 45 000; Plein temps

Résumé du poste

A prestigious university in France is seeking a First Stage Researcher (PhD candidate) to improve a multi-agent simulator for anticipating adverse events in operating rooms. The candidate will work on connecting the simulator to operating room sensors, developing data acquisition and forecasting algorithms, and raising alerts in risky situations. Those with a Master's degree in computer science and experience with multi-agent systems are encouraged to apply. This full-time position begins on January 1, 2026.

Qualifications

• Prior experience in data acquisition and processing algorithms is beneficial.
• Familiarity with algorithms for event forecasting is advantageous.

Responsabilités

• Study the scientific literature on adverse events in operating rooms.
• Develop a connection between the simulator and sensors in the operating room.
• Implement data acquisition and processing algorithms within the simulator.
• Develop forecasting algorithms to anticipate adverse events.
• Trigger alerts in the operating room in case of risky situations.

Connaissances

Experience with multi-agent systems

Formation

Master Degree or equivalent

Description du poste

Organisation/Company Université Marie et Louis Pasteur

Research Field Computer science

Researcher Profile First Stage Researcher (R1) Positions PhD Positions

Country France Application Deadline 4 Dec 2025 - 23:59 (Europe/Paris)

Type of Contract Temporary Job Status Full-time Hours Per Week 35:00 Offer Starting Date 1 Jan 2026 Is the job funded through the EU Research Framework Programme? Interreg Is the Job related to staff position within a Research Infrastructure? No

Offer Description

This thesis is part of the SSUWAI project, which aims to anticipate and thus prevent adverse events in the operating room. An existing multi-agent simulator is already in place, but this thesis aims to improve it in several ways. The first improvement involves establishing a connection between the simulator and sensors located in the operating room. This will require implementing data acquisition algorithms and data processing algorithms within the simulator. The second point concerns the anticipation of adverse events. To achieve this, the simulator will need to simulate numerous scenarios based on the current situation and will also rely on forecasting algorithms. The simulator must also enable action to be taken in the operating room by triggering an alert in the event of a risky situation. The question arises of using AI to optimize the simulator’s ability to anticipate events. All of this must be carried out following an in-depth review of the scientific literature.

Main supervisor: Dr. Christophe Lang (UMLP)

Objectives

1. Study the scientific literature
2. Develop a connection between the simulator and sensors located in the operating room
3. Develop data acquisition algorithms and data processing algorithms within the simulator
4. Develop forecasting algorithms
5. Raise alerts in the operating room

Where to apply

E-mail [e-mail]

Requirements

Research Field Computer science Education Level Master Degree or equivalent

Skills/Qualifications

It is a bonus if the candidate had already worked with multi-agent systems.