PhD position

**Job Description**
This Ph.D. position focuses on developing a health condition monitoring system for older adults after hip fracture surgery to reduce complications and mortality rates. The researcher will develop physiological-model-based artificial intelligence technologies using multimodal physiological signals (e.g., inertial measurement unit (IMU), electrocardiography (ECG), photoplethysmogram (PPG), Electrodermal activity (EDA), and contactless movement and physiology signals) to assess patient recovery and predict adverse clinical events like delirium, cardiac arrhythmias, and pneumonia. The role also involves designing medical research experimental protocols for both healthy control and target patient populations, obtaining ethical approval, and performing approved experiments. This position is embedded within the EU Horizon Europe Marie Sklodowska-Curie Doctoral Network (MSCA DN) SMARTTEST project, specifically linked to Doctoral Candidate 8 (DC08).

**Skills & Abilities**
• Expertise in multimodal physiological signals processing (e.g., IMU, ECG, PPG, EDA).
• Strong background in physiological-model-based artificial intelligence technologies.
• Ability to design and execute medical research experimental protocols.
• Knowledge of ethical regulations and approval processes in medical research.

**Qualifications**
Required Degree(s) in:
• Master’s degree in Biomedical Engineering
• Master’s degree in Artificial Intelligence
• Master’s degree in Electrical Engineering
• Master’s degree in Computer Science
• Master’s degree in a related relevant field

**Experience**
Other:
• Expected to perform high quality and internationally visible research.
• Close collaboration with an interdisciplinary team and project partners.

Note: We’ve analyzed the actual job post using AI, for more details visit the original job post by clicking on “Apply Now”!