PhD Fellowship: Cardiac Digital Twin & Echo Modelling

Espen Remme; Oslo; On-site; NOK 520,000 - 600,000; Full time

Benefits offered by this job

Standard Norwegian PhD salary

International environment

Professional development

Attractive welfare arrangements

Job summary

Oslo University Hospital's Intervention Centre invites applications for a 3-year PhD-fellowship, funded under the MSCA program. The project links echocardiography with digital twin modelling to assess diastolic function, with stays planned at international partner institutions.

The fellow will develop and validate computational models, analyze clinical datasets, and contribute to the clinical utility of diastolic assessment tools in a multidisciplinary team.

Qualifications

• Strong academic record with a weighted average grade of B or higher.
• Experience with scientific programming (Python, MATLAB) is advantageous.
• Interest in interdisciplinary research at the interface of engineering, mathematics and medicine.

Responsibilities

• Develop mathematical models linking echocardiographic data to heart physiology and mechanics.
• Integrate imaging data with computational models to estimate key clinical parameters.
• Collect and analyze animal and clinical datasets with invasive data when needed.
• Collaborate in an interdisciplinary team for model validation and clinical translation.

Skills

Interdisciplinary research

Scientific programming

English communication

Independent work in multidisciplinary팀

Cardiovascular physiology interest

Education

Master's degree in Cybernetics, Electrical Engineering, Informatics, Physics, Mathematics, Biomedical Engineering, Medical Technology

Tools

Python

MATLAB

Job description

Oslo University Hospital's Intervention Centre invites applications for a 3-year PhD-fellowship, funded under the MSCA program. The project links echocardiography with digital twin modelling to assess diastolic function, with stays planned at international partner institutions.

The fellow will develop and validate computational models, analyze clinical datasets, and contribute to the clinical utility of diastolic assessment tools in a multidisciplinary team.