Job Summary

The Division of Cardiovascular Medicine at the University of Michigan is expanding a nationally and internationally funded research program at the cutting edge of cardiovascular medicine. Led by Drs. Venkatesh Murthy and Sascha Goonewardena - whose work has appeared in leading journals including NEJM AI, JAMA, and Circulation - the program fuses artificial intelligence, advanced cardiac imaging, multiomics (proteomics, metabolomics, and genomics), and cardiometabolic disease biology to develop precision diagnostics and identify novel therapeutic approaches, with a particular focus on coronary microvascular disease and other cardiovascular conditions that disproportionately affect women and remain poorly served by existing diagnostic tools. This is a rare opportunity to join a high-impact, well-funded program doing science that matters.

This position serves as the primary AI and ECG computational scientist for the program. The incumbent will build and train deep learning foundation models and drive the computational work that connects cardiac electrical signatures to biological disease mechanisms. This is an engineering and infrastructure-focused role; the incumbent builds and optimizes the models and data systems that power the program's AI-driven analyses. This is one of two senior data scientist roles; the two positions serve complementary, non-overlapping functions.

Responsibilities*

• Develop, train, and refine deep learning foundation models (including transformer and self-supervised architectures) for ECG-based detection and endotyping of cardiometabolic disease
• Assemble, harmonize, clean, and catalog large-scale, heterogeneous ECG datasets from multiple internal and external sources and formats
• Build and maintain reproducible data processing pipelines, data loaders, and PostgreSQL-based data management infrastructure
• Evaluate model performance, document methods, and prepare written and code-based analytical reports (Python)
• Contribute to manuscripts, grant reports, and presentations
• Collaborate with collaborative network partners and other research collaborators on code, computational workflows, and data harmonization
• Other duties as assigned

Required Qualifications*

• Masters or doctoral degree in computer science, electrical engineering, biomedical engineering, computational biology, statistics with an AI/ML focus, data science, or a closely related quantitative field
• Demonstrated experience developing and training deep learning models, preferably in a biomedical or physiological signal context
• Proficiency in Python and deep learning frameworks (PyTorch preferred; TensorFlow acceptable)
• Experience with large-scale, heterogeneous data harmonization and processing pipelines spanning multiple source formats
• Familiarity with self-supervised, semi-supervised, or foundation model architectures (e.g., transformers, masked autoencoders)
• Proficiency in SQL, preferably PostgreSQL, for data querying and management
• Experience with high-performance computing environments, including Slurm-based job scheduling
• Strong organizational skills and attention to detail
• Ability to prepare and present written and code-based (Python or R) analytical reports
• Strong scientific communication skills; ability to contribute to manuscripts and grant reports

Desired Qualifications*

• Experience with electrocardiographic (ECG) or other physiological waveform data
• Experience with multimodal data integration, particularly combining physiological signals with cardiac imaging data
• Familiarity with clinical data infrastructure (EHR, DICOM, HL7/FHIR)
• Experience with transfer learning or domain adaptation across heterogeneous datasets
• Track record of peer-reviewed publications or preprints in machine learning, AI, or biomedical informatics
• Familiarity with cardiovascular physiology or cardiology research
• Experience with Git and reproducible research practices
• Familiarity with cloud computing environments (AWS, GCP, or Azure)

What Benefits can you Look Forward to?

• Excellent medical, dental and vision coverage effective on your very first day
• 2:1 Match on retirement savings

Modes of Work

Positions that are eligible for hybrid or mobile/remote work mode are at the discretion of the hiring department. Work agreements are reviewed annually at a minimum and are subject to change at any time, and for any reason, throughout the course of employment. Learn more about the work modes .

Work Schedule

Work Schedule: Monday through Friday, standard business hours. This is an onsite position.

Additional Information

We, the staff and faculty of the U-M Cardiovascular Center (CVC) team, are committed to advancing medicine and serving humanity through living and teaching our core values of Respect and Compassion; Collaboration; Innovation; and Commitment to Excellence. Each CVC employee is expected to understand and demonstrate that in every interaction we represent our entire organization in the care we provide and in the courtesies we extend to patients, families, and each respective team member. The CVC is dedicated to partnering with patients and families to deliver the safest and highest quality of health care.

The Division of Cardiovascular Medicine is firmly committed to advancing inclusion, diversity, equity, accessibility, and belonging, which are core to the culture and values of the Medical School Office of Research. Our community supports recruiting and cultivating a diverse workforce as a reflection of our commitment to serve the diverse people of Michigan and the world. We strive to create a work culture where each team member feels respected, valued, and safe.

Application Deadline

Job openings are posted for a minimum of seven calendar days. The review and selection process may begin as early as the eighth day after posting. This opening may be removed from posting boards and filled anytime after the minimum posting period has ended.

Job Detail

Job Opening ID

280229

Working Title

Senior Data Scientist - AI and ECG

Job Title

Bioinfo-Comput Biologist Sr

Work Location

Ann Arbor Campus

Ann Arbor, MI

Modes of Work

Onsite

Full/Part Time

Full-Time

Regular/Temporary

Regular

FLSA Status

Exempt

Organizational Group

Medical School

Department

MM Int Med-Cardiology

Posting Begin/End Date

7/30/2026 - 8/27/2026

Career Interest

Research