Data Science & AI Innovation Postdoctoral Fellow

We are excited to invite applications for the Novartis Biomedical Research Postdoctoral Fellowship Program; a unique training opportunity designed for exceptional early-career scientists eager to tackle some of the most challenging problems in biomedical research and drug discovery. As a Postdoctoral Research Fellow, you will join the Cardiovascular and Metabolism disease area in Cambridge and pursue an innovative research project at the forefront of biomedical science and drug discovery.

You will work alongside leading scientists in a highly collaborative, multidisciplinary environment while gaining exposure to the broader ecosystem that translates scientific discovery into medicines. Our fellows are empowered to ask bold scientific questions, apply cutting-edge technologies, and develop approaches that have the potential to transform patient care.

Internal

Job Title:

Discovery Postdoctoral Fellow

Position Location:

Cambridge, MA, onsite #LI-onsite

• This position is not eligible for visa sponsorship.
• Please note that relocation support is not available for this position.
• This is a full-time training position of up to three years in duration.
• The start date for the 2026 Novartis   Postdoctoral Fellowship Program cohort is October 1, 2026. Please confirm your availability to meet this date in your cover letter.

As a Data Science & AI Innovation Fellow, you will:

• Develop and apply multimodal AI/ML models and statistical methods to integrate ECG, genomic, and proteomic data for cardiovascular disease research.
• Analyze large-scale multimodal datasets from biobanks, clinical studies, and real-world data sources to identify novel biomarkers and disease mechanisms.
• Design, implement, and evaluate predictive and interpretable models linking physiological signals with molecular and genetic variation.
• Collaborate with a multidisciplinary team of data scientists, geneticists, clinicians, and cardiovascular researchers.
• Communicate findings through publications, conference presentations, and internal scientific seminars.

The Novartis Biomedical Research Postdoctoral Fellowship Program is designed to develop the next generation of scientific leaders and power the future of medicine through rigorous research, and immersive learning experiences, including the implementation of AI tools in biomedical research.

• Guidance from accomplished scientific leaders and subject matter experts
• Access to advanced technologies, platforms, and research capabilities
• Collaboration across disciplines and organizational boundaries
• A global and diverse community of postdoctoral fellows
• Dedicated programming designed to help fellows thrive throughout their careers.
• Personalized experiential learning opportunities through a Postdoc Practicum that empowers fellows to explore new scientific domains, build cross-functional expertise, and expand their impact beyond their primary research project.
• Opportunities to present research, publish in leading journals, and build an international scientific network.

Analytical Thinking, Chemical Biology, Chemistry, Clinical Research, Clinical Trials, Collaboration, Curious Mindset, Data Analysis, Detail-Oriented, Ethics, Gene Therapy, Immunology, Machine Learning (ML), Mammalian Cell Culture, Medical Research, Molecular Biology, Patient Care, Science Improving the lives of people living with disease takes more than innovative science. It takes a focus on the needs of people and a community committed to meeting them.

It takes a team of people like you. Working together. Learning together. Thriving together. Discover how you can join us in changing people’s lives.

• PhD (or equivalent doctoral degree) in a relevant scientific discipline completed prior to the fellowship start date. The program is intended for scientists immediately following their PhD training (PhD conferred in 2026 only).
• Demonstrated record of scientific achievement (publications, presentations, patents, or equivalent)
• Strong commitment to learning, innovation, and professional development
• Strong quantitative background in data science, statistics, machine learning, bioinformatics, computational biology, computer science, biomedical engineering, or a related field.
• Programming proficiency in Python and/or R and experience working with large-scale datasets.
• Hands-on experience applying statistical or machine learning methods to…