Researcher in Deep Learning and Biomedical Signal Analysis

Université de Caen Normandie; France; On-site; EUR 24,000 - 36,000; Full time

Job summary

Université de Caen Normandie, GREYC research unit, Caen, France, seeks a First Stage Researcher (R1) to develop and optimize AI models for non-invasive cardiac monitoring using ECG/SCG signals. You will work under project supervision with CardiaMetrics collaboration.

Ideal candidates hold a Master 2 or PhD in AI/ML, with biomedical signal experience and strong English proficiency, and will contribute to publications and international conferences.

Qualifications

• Master 2 in Computer Science, an Engineering degree, or a PhD in AI/ML.
• Experience with biomedical signals (ECG/SCG) is preferred.
• Fluent English in written and spoken form.

Responsibilities

• Data engineering: describe, prepare and preprocess multi-source clinical databases (ECG/SCG).
• R&D: optimize architecture for intracardiac pressure regression and improve sensitivity.
• Validation and interpretability: conduct rigorous tests and XAI studies.
• Dissemination: draft scientific articles and present at conferences.

Skills

Data engineering

Model development

Research & development

Explainability (XAI)

Data preprocessing

Education

Master's degree in CS

Engineering degree

PhD in AI/ML

Tools

Python

TensorFlow

SCG/ECG analysis

Job description

Organisation/Company Université de Caen Normandie Research Field Computer science Engineering Researcher Profile First Stage Researcher (R1) Positions Other Positions Application Deadline 9 Oct 2026 - 23:59 (UTC) Country France Type of Contract Temporary Job Status Full-time Offer Starting Date 12 Oct 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

Project:Normandeep M-Pulse (CardiaMetrics Partnership)
Field:Artificial Intelligence, Signal Processing, Digital Health (MedTech)
Location:University of Caen Normandy – GREYC Laboratory UMR 6072
Education Level:Master 2, Engineering Degree (Master’s level) or PhD in Computer Science

1. Project Context

Chronic Heart Failure (CHF) affects more than 1.5 million people in France and is the leading cause of hospitalization for those over 65. The major challenge lies in the unpredictable nature of "decompensation" phases. Currently, detecting increases in intracardiac pressure — the precursors of a crisis — requires invasive examinations in a hospital setting.

The Normandeep M-Pulse project aims to transform this monitoring through the MyHeartSentinel system, consisting of a subcutaneous implant developed by the company CardiaMetrics. This implant records two types of key signals: the electrocardiogram (ECG) and the seismocardiogram (SCG).

The challenge is to develop an intelligent architecture capable of estimating intracardiac pressures from these signals, thereby enabling non-invasive, preventive, at-home monitoring.

2. Missions and Responsibilities

Under the supervision of the project managers and in close collaboration with the CardiaMetrics teams, you will work on the development and optimization of the model. Your main missions will be:

• Data Engineering:Description, preparation, and preprocessing of multi-source clinical databases (ECG and SCG signals from various pathological profiles).
• Research and Development:
  • Optimization of the existing architecture for intracardiac pressure regression.
  • Improvement of model sensitivity (detection of fine variations of ±3 mmHg).
  • Research into inter-patient robustness (management of variability related to age, morphology, and comorbidities).
• Validation and Interpretability:
  • Conducting rigorous tests to validate clinical performance.
  • Explainability studies (XAI) and physiological correlation analysis to guarantee the medical reliability of the algorithm.
• Scientific Dissemination:Drafting scientific articles and presenting work at international conferences and specialized congresses (digital health, AI, cardiology).

Requirements

Research Field Computer science Education Level Master Degree or equivalent

Skills/Qualifications

Education:

• Holder of a Master 2 in Computer Science, an Engineering Degree, or a PhD specialized in AI, Signal Processing, or Applied Mathematics and Digital Health.

Desired Skills:

• Experience in the biomedical field (knowledge of ECG/SCG signals).
• Fluency in scientific English (written and oral).

Personal Qualities:

• Strong motivation for health challenges and medical innovation.
• Autonomy, scientific rigor, and intellectual curiosity.
• Ability to work in a collaborative environment (research/industry interface).
• Remuneration:According to profile and experience (institutional pay scale).

Work Location(s)

Number of offers available 1 Company/Institute Université de Caen Normandie - GREYC research unit Country France City Caen Postal Code 14000 Street 6 Boulevard du Maréchal Juin Geofield