Health AI Scholar; Spring​/Summer

Samsung Research America Digital Health Algorithms Team  collaborates with top universities, hospitals, and healthcare‑industry partners to collect large‑scale data and develop novel AI/ML algorithms to transform how healthcare is delivered. We use design thinking to address some of healthcare’s toughest challenges, from improving care and producing better outcomes, to reducing costs and expanding access.

Focusing on wearable, mobile, and cloud‑based form factors, our multi‑disciplinary team develops innovative technologies that we then turn into groundbreaking commercial products to support clinicians, patients, and consumers. We use advanced sensor technology to capture physiologic responses and make use of our AI/ML framework to build algorithms for developing digital biomarkers and digital interventions. We employ data analytics to supplement clinical care and facilitate remote patient monitoring, thereby helping patients make behavioral changes that improve their health and daily lives.

Our work has been internationally recognized with 70+ peer‑reviewed publications and 10 design awards.

Our portfolio of digital health algorithmic solutions are important tools in helping clinicians and their patients monitor and manage serious health conditions, such as cardiovascular disease, pulmonary disease, and cancer; as wells chronic illnesses including mental health, diabetes, hypertension, depression, sleep disorders, and obesity. Our work encompasses the entire range of processes, from ideating, developing, and incubating; to designing and delivering market‑ready products;

to supporting and evolving currently released products.

We are looking for a highly motivated and talented individual with solid ML/AI/GenAI technology background to join the Digital Health Algorithms Team as a Health AI Scholar for a 10‑month residency program. This position is ideal for a fresh graduate PhD student or a postdoctoral researcher with digital health research experience in multi‑modal physiological time series algorithm development and passionate about applying cutting‑edge artificial intelligence techniques to health‑related challenges.

You will have the opportunity to work alongside a diverse and innovative team, leveraging your expertise to advance our AI‑driven health initiatives.

Samsung’s unique advantage in the consumer electronics market and growing focus on digital health will provide you with unprecedented large data sets and healthcare analytics challenges.

• Design, implement, and optimize advanced AI models, including self‑supervised learning, for health applications.
• Work with large‑scale time‑series datasets, developing robust algorithms to extract meaningful insights.
• Collaborate with multidisciplinary teams to translate AI‑driven insights into impactful healthcare solutions.
• Train and fine‑tune deep learning models using AWS AI services, ensuring scalability and efficiency.
• Contribute to the development of novel AI methodologies to address complex healthcare challenges.
• Actively engage in team discussions, fostering a collaborative and inclusive work environment.

• PhD (near completion) or postdoctoral experience in Computer Science, Artificial Intelligence, Machine Learning, Biomedical Engineering, or a related field.
• Strong expertise in deep learning techniques (e.g., self‑supervised learning, transformer architectures, CNNs, RNNs).
• Proven experience working with time‑series datasets, preferably in health‑related domains.
• Proficiency in developing and deploying models using AWS AI services including Sage Maker and Redshift.
• A track record of peer‑reviewed publications in top AI/health‑related journals or conferences.
• Programming using languages such as Python, R, Android, C/C++, Java.
• Demonstrated ability to work collaboratively in multidisciplinary teams.

$62 — $75 USD

Disclosure of Trade Secrets

Samsung has a strict policy on trade secrets. In applying to Samsung and progressing through the recruitment process, you must not disclose any trade secrets of a current or previous employer.

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