Careers
Join our team
We are looking for exceptional team members to join our revolution in digital health! HPI·MS is calling on all those with a passion for improved healthcare and translational data science to share their knowledge and expertise with an international community motivated by the same call to action.
Current Opportunities
Postdoctoral Researcher - mHealth (AI & Human Health - Ensari Lab)
The Windreich Department of Artificial Intelligence and Human Health within the Icahn School of Medicine at Mount Sinai is searching for a postdoctoral research scientist to join Dr. Ensari’s research laboratory. Our group conducts research in the intersection of biomedical informatics, artificial intelligence, and women’s health, toward developing and implementing machine learning models to patient-generated health data.
Learn morePostdoctoral Researcher - Multimodal Healthcare Data (AI & Human Health - Fuchs Lab)
The Windreich Department of AI & Human Health at Mount Sinai is inviting applications for a Postdoctoral Research Fellowship position in the novel field of multi-modal healthcare data.
Learn morePostdoctoral Researcher - Computational Pathology (AI & Human Health - Fuchs Lab)
The Thomas Fuchs Lab at the Windreich Department of AI & Human Health at Mount Sinai is inviting applications for a Postdoctoral Research Fellowship position in the novel field of computational pathology using supervised, weakly supervised, and unsupervised machine-learning algorithms and methods with applications in healthcare.
Learn moreSenior Product Manager - AI-Ready Mount Sinai (AIR.MS)
The Windreich Department of AI & Human Health is inviting applications for a Senior Product Manager to lead the development and success of ongoing initiatives, which aim to enable biomedical research using rich health data and AI.
Learn moreData Engineer II - Computational Pathology (AI & Human Health - Fuchs Lab)
The Thomas Fuchs Lab at the Windreich Department of AI & Human Health at Mount Sinai is inviting applications for a Data Engineer position in the novel field of computational pathology using supervised, weakly supervised, and unsupervised machine-learning algorithms and methods with applications in healthcare
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