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# Postdoctoral Data Science Research Fellowship

- **Company:** Mount Sinai Health System
- **Location:** New York, NY, United States
- **Salary:** $74,692.0 - $80,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Health Informatics, Computer Programming, Python (Programming Language), Machine Learning, Tensorflow, Graph Neural Networks, Pytorch, Deep Learning, Keras
- **Published:** October 13, 2026
- **Apply:** https://www.juju.com/job/1_mtsinai-3040737

## About the Role

Significant experience in machine learning techniques is preferred, ideally with published work and/or code available.
Expertise with CNNs, Transformers, ECG embeddings, GNNs, and Deep Learning frameworks is preferred (e.g. d3rlpy, Tensorflow, PyTorch, Keras).
3.
Expertise with programming and statistical software experience with advanced Python proficiency.
4.
A strong statistics, data science, and/or engineering background is advantageous.
5.
The ideal candidate will have a track record of academic publication and likes to be creative.
6.
Strong communication and presentation skills with fluency in spoken and written English. **About Us** **Strength through Unity and Inclusion** The Mount Sinai Health System is committed to fostering an environment where everyone can contribute to excellence.

## Description

Actual salaries depend on a variety of factors, including experience, education, and operational need.
The salary range or contractual rate listed does not include bonuses/incentive, differential pay or other forms of compensation or benefits.
SPOC-UAW Local 4100 at Icahn School of Medicine (Post Docs), J18 - AI and Human Health - ISM, Icahn School of Medicine **Responsibilities** We have a specific interest in applications for cardiovascular disease and applications to novel device technologies.
The postdoctoral fellow will join a dynamic team of data scientists, engineers, and clinicians.
They will participate in unique opportunities to apply deep learning for important scientific breakthroughs that are scalable, clinically meaningful, and operationally pragmatic.
The ideal candidates will have the following background: 1.
PhD, MD/PhD in a quantitative science-related field (e.g., biomedical informatics, clinical informatics, machine learning, biostatistics, etc.).
2.