Health AI Innovator — Digital Health Algorithms

Samsung Research America (SRA); Mountain View (CA); On-site; USD 85,000 - 103,000; Full time

Job summary

Samsung Research America’s Digital Health Algorithms Team is seeking a Health AI Scholar for a 12-month residency in Mountain View, starting January 2027. This role is ideal for a PhD student in year 3 or a postdoc with digital health research in multi-modal physiological timeseries.

You will design and optimize AI models, work with large-scale datasets, and deploy solutions using AWS SageMaker, contributing to health biomarkers and interventions while collaborating across disciplines in a

Qualifications

• PhD (near completion) or postdoctoral experience in Computer Science, AI, ML, Biomedical Engineering, or related field.
• Strong expertise in deep learning techniques (self-supervised learning, transformers, CNNs, RNNs).
• Proven experience with time-series datasets, preferably in health domains.
• Proficiency deploying models using AWS AI services including SageMaker and Redshift.
• Peer-reviewed publications in AI/health journals or conferences.

Responsibilities

• Design, implement, and optimize advanced AI models, including self-supervised learning, for health applications.
• Work with large-scale time-series and tabular datasets to extract meaningful insights.
• Build frameworks for discovering health biomarkers.
• Collaborate with multidisciplinary teams to translate AI insights into healthcare solutions.
• Train and fine-tune deep learning models using AWS AI services for scalability and efficiency.
• Contribute to development of novel AI methodologies for health challenges.
• Engage in team discussions to foster collaboration.

Skills

Deep learning

Time-series data

AWS SageMaker

Python

Education

PhD (near completion) or postdoctoral

Tools

AWS Redshift

Python

Job description

Samsung Research America’s Digital Health Algorithms Team is seeking a Health AI Scholar for a 12-month residency in Mountain View, starting January 2027. This role is ideal for a PhD student in year 3 or a postdoc with digital health research in multi-modal physiological timeseries.

You will design and optimize AI models, work with large-scale datasets, and deploy solutions using AWS SageMaker, contributing to health biomarkers and interventions while collaborating across disciplines in a