Data Science & AI Innovation Postdoctoral Fellow
Core
Develop and apply multimodal AI/ML models to integrate ECG, genomic, and proteomic data for cardiovascular disease research and drug discovery.
Role type
Postdoctoral Research Fellow (Data Science & AI)
Builds
Predictive models linking physiological signals with molecular and genetic variation for future therapies
Domain
Biomedical research / Cardiovascular disease / Drug discovery
Deliverable
production ML models
Required skills
Python, R, statistical methods, machine learning, bioinformatics, large-scale dataset analysis, predictive model evaluation
Preferred skills
statistical genetics, multi-omics analysis, deep learning, foundation models for biomedical data, ECG signal analysis
Technologies
Python, R
Responsibilities
Develop multimodal AI/ML models to integrate ECG, genomic, and proteomic data; Analyze large-scale multimodal datasets from biobanks and clinical studies to identify biomarkers; Design and evaluate interpretable models linking physiological signals with genetic variation; Collaborate with multidisciplinary teams of data scientists, geneticists, and clinicians; Communicate findings through publications and conference presentations
Seniority
Postdoctoral Fellow (early-career scientist immediately following PhD)
