PhD Candidate - Cardiac Electromechanical Modeling

Euro Math Soc; Graz; On-site; EUR 30,000 - 40,000; Full time

Job summary

A leading academic institution in Austria is seeking a PhD student to join the Young Research Group focused on cardiac modeling. The project, funded by BioTechMed-Graz, aims to develop methodologies for subject-specific calibration of cardiac electromechanical models. Successful candidates should have a strong background in applied mathematics, physics, or engineering, and experience with machine learning. Responsibilities include extending inverse problem methods and integrating clinical data. This position offers a unique opportunity to contribute to innovative research in cardiovascular function.

Qualifications

• Strong background in applied mathematics or physics.
• Experience with computational modeling or machine learning.
• Knowledge of cardiovascular function and biophysical parameters.

Responsibilities

• Extend the inverse problem method to accurately model cardiovascular function.
• Integrate real clinical data for assessment.
• Apply methodology to evaluate cardiac tissue scars.

Skills

Computational modeling

Physics-informed machine learning

Inverse problem methodology

Education

Master's degree in applied mathematics, physics, or related field

Job description

A leading academic institution in Austria is seeking a PhD student to join the Young Research Group focused on cardiac modeling. The project, funded by BioTechMed-Graz, aims to develop methodologies for subject-specific calibration of cardiac electromechanical models. Successful candidates should have a strong background in applied mathematics, physics, or engineering, and experience with machine learning. Responsibilities include extending inverse problem methods and integrating clinical data. This position offers a unique opportunity to contribute to innovative research in cardiovascular function.