Secure Wireless Localization and Sensing for Digital Health

European Commission; France; Sur place; EUR 30 000 - 60 000; Plein temps

Résumé du poste

An established industry player is seeking a PhD candidate to join an innovative project focused on secure vital signs and location estimation using cutting-edge RF sensing technology. This exciting opportunity involves analyzing complex channel properties and developing advanced machine learning techniques to enhance healthcare diagnostics. The role promises to be at the forefront of technological advancements, contributing to significant improvements in privacy-preserving health monitoring. If you are passionate about engineering and eager to make a meaningful impact in healthcare, this position is perfect for you.

Qualifications

• Master's degree in signal processing, IoT, or machine learning required.
• Familiarity with programming languages like Python, R, and Matlab is essential.

Responsabilités

• Conduct research on secure vital signs and location estimation.
• Develop machine learning techniques for motion-robust vital signs estimations.

Connaissances

Python

R

Matlab

Interpersonal Skills

Communication Skills

Formation

Master Degree in Signal Processing or Relevant Area

Description du poste

Organisation/Company: ETIS Laboratory (UMR 8051), CY Cergy Paris Université, ENSEA, CNRS

Research Field: Engineering » Communication engineering

Researcher Profile: Recognised Researcher (R2), Leading Researcher (R4), First Stage Researcher (R1), Established Researcher (R3)

Country: France

Application Deadline: 29 Jun 2025 - 22:00 (UTC)

Type of Contract: Temporary

Job Status: Full-time

Offer Starting Date: 1 Oct 2025

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

The PhD candidate will work on the ANR funded JCJC project SecLoc, which is entitled “Secure vital signs and location estimation: A smart health vision via RF sensing”. The project positions itself at the technological forefront, aiming to tackle the challenges of privacy-preserving real-time multi-target joint vital signs and location estimations in dynamic residential contexts, thus providing clinical-level insights for early diagnosis and therapeutic intervention by healthcare professionals. Three main objectives will be covered in this project:

1. By analyzing sophisticated channel properties, accurate location determination can be achieved through a pervasively available and low-cost Wi-Fi fingerprinting scheme.
2. Meanwhile, mmWave MIMO radars will be exploited to carry out motion-robust context-adaptive vital signs estimations (i.e., respiration and heartbeat) by developing beyond state-of-the-art machine learning techniques.
3. An innovative seamless and secure data fusion strategy along with reconfigurable intelligent surfaces will be investigated, designed, and validated in multiple realistic scenarios, boosting capabilities for both localization and sensing.

Funding category: Contrat doctoral

ANR

PHD Country: France

Minimum Requirements

Applicants must have a master degree in a relevant area, e.g., signal processing for wireless communications, IoT systems/technologies, machine learning based radio applications. He/She should be familiar with key engineering programming languages (e.g., Python, R, Matlab, etc.). Strong interpersonal and communication skills, and the ability to work effectively in a team are essential. An advanced level of the English language is required.

Additional Information

Work Location(s)

Number of offers available: 1

Company/Institute: ETIS Laboratory (UMR 8051), CY Cergy Paris Université, ENSEA, CNRS

Country: France

City: Cergy