Project description

Atrial fibrillation (AF) is a complex cardiac arrhythmia with multifactorial causes and poses significant global healthcare challenges due to increased morbidity, mortality, and healthcare costs. The TrackAF project will train 15 researchers to address gaps in our understanding of AF, atrial cardiomyopathy (ACM) their management and consequences by integrating advanced data-driven and mechanistic computational modelling, clinical AI and wet-lab research with a focus on extended time scales of AF etiology and progression. Systematic identification of the longitudinal effects of age and sex on AF progression and treatment outcomes remains challenging. The 2024 European AF guidelines highlight evidence gaps, including the variability in AF and ACM evolution and the need for personalized risk prediction. TrackAF will bridge these gaps through a comprehensive, interdisciplinary and intersectoral research and training program to develop innovative approaches to AF prevention, diagnosis and treatment, supporting key health policies and contributing to the UN's Sustainable Development Goals. Our objectives include enhancing AF prediction and risk stratification using novel biomarkers, refining diagnostic techniques by multimodal stratification and improving acute and long-term management and treatment outcomes through integration of mechanistic and data-driven decision-support models.

TrackAF's doctoral training will produce medical scientists with expertise in AF through a balanced structure of core research, formal training and practical secondments. This interdisciplinary approach gives doctoral candidates the ideal preparation for diverse career paths in medical science by integrating technical, ethical and legal aspects of medical research to foster innovation and collaboration across academia, industry and healthcare. The TrackAF outcomes will contribute to reducing the burden of AF and thereby improve patient quality of life across Europe and beyond.

Fields:

• Biomedical engineering
• Clinical data science
• Biology
• Machine learning, statistical data processing and applications using signal processing
• Medical engineering and technology
• Numerical analysis, simulation, optimization, modelling tools
• Scientific computing and data processing
• Biological systems analysis, modelling and simulation

Keywords: atrial fibrillation, atrial cardiomyopathy, in silico medicine, in silico trials, virtual cohorts, clinical data science, electrocardiography, digital twin

Requirements

• University degree (Master or equivalent, 5 years) in a relevant field of study for the respective DC project
• Willingness to travel for at least wo secondments and collaborative activities within the TrackAF network
• Openness to collaborate in a truly interdisciplinary network ranging from wet lab biology to advanced computational methods and artificial intelligence.
• Fluency in written and spoken English
• Good organization and communication skills

Eligibility criteria

• The applicant must have a university degree (MSc degree or equivalent).
• The applicant must not already be in possession of a doctoral degree at the date of the recruitment. Researchers who have successfully defended their doctoral thesis but have not yet formally been awarded the doctoral degree will not be considered eligible. The eligibility of the researcher will be determined at the date of their first recruitment in the action.
• MSCA Mobility Rule: At the time of recruitment, the researcher must not have resided or carried out their main activity (work, studies, etc.) in the country of the recruiting beneficiary (‘Host institution’) for more than 12 months in the three years immediately prior to the recruitment date. Compulsory national service and/or short stays such as holidays are not considered.

Applicants who do not fulfill the Mobility Rule or other Eligibility Criteria CANNOT be considered for the research position.

Applicants can be of any nationality within laws of EU to enter the EU countries.

Candidates may apply prior to obtaining their Master’s degree but cannot receive an employment contract before having obtained the Master’s degree.

Candidates may apply to multiple positions offered within TrackAF and should carefully choose the ones that they apply for.

Selection process

• Applications will be reviewed for eligibility and suitability based on the criteria listed for each position.
• After shortlisting, candidates will be invited for online interviews with the respective recruitment committees.
• The recruiting institution will send out notification of the selection outcome after the online interview.

The following timeline is expected:

• May 2026: interviews of the shortlisted candidates
• June 2026: information to the applicants
• July-August 2026: hiring process
• 1st September 2026: desired start of the contract