Principal Research Scientist – Healthcare Algorithms

About Analog Devices

Analog Devices, Inc. (NASDAQ: ADI ) is a global semiconductor leader that bridges the physical and digital worlds to enable breakthroughs at the Intelligent Edge. ADI combines analog, digital, and software technologies into solutions that help drive advancements in digitized factories, mobility, and digital healthcare, combat climate change, and reliably connect humans and the world. With revenue of more than $9 billion in FY24 and approximately 24,000 people globally, ADI ensures today's innovators stay Ahead of What's Possible™. Learn more at www.analog.com and on LinkedIn and Twitter (X).

The Analog Garage is ADI’s Research and Advanced Development Center in downtown Boston and empowers ADI by pioneering breakthrough technologies. The Algorithmic Solutions Group within Analog Garage researches and develops cutting-edge, efficient algorithms to convert data into intelligence that solves society’s most important problems. The team leverages its experience in the fields of signal processing, computer vision, computational linguistics, machine learning, artificial intelligence, communication systems, and other areas of electrical engineering and computer science to create impactful solutions.

The Analog Garage is ADI’s Research and Advanced Development Center in downtown Boston and empowers ADI by pioneering breakthrough technologies. The Algorithmic Solutions Group within Analog Garage researches and develops cutting-edge, efficient algorithms to convert data into intelligence that solves society’s most important problems. The team leverages its experience in the fields of signal processing, machine learning, artificial intelligence, computer vision, computational linguistics, communication systems, and other areas of electrical engineering and computer science to create impactful solutions.

The Algorithmic Solutions Group is seeking a highly motivated Principal Research Scientist to advance healthcare solutions with cutting-edge algorithms. The ideal candidate should bring real-world experience with physiology and biomedical datasets, enabling informed decision-making throughout the product development lifecycle, including experimental design, sensor placement, data pre-processing, and algorithm development and validation. ADI leads in high-performance sensors integrated into healthcare and wellness products. As a research scientist, you will combine advanced hardware and sophisticated algorithms to bring intelligence to the edge, creating new opportunities for patient care and biomedical research, including remote monitoring and decentralized clinical care. Join ADI now to be part of a pioneering team transforming global health through innovation.

Responsibilities include:

• Collaborate with cross-functional teams, inside and outside the Algorithmic Solutions Group, to connect our work with our mission statement.
• Identifying domains within health sciences where ADI can drive innovation to benefit human health.
• Collaborate with hardware and firmware engineers to facilitate the design and collection of novel biosensing datasets.
• Conceptualize, design, and implement cutting-edge algorithms for analyzing complex human physiological data.
• Conduct validation studies to confirm the efficacy and accuracy of developed algorithms, ensuring they can be effectively integrated into healthcare solutions.  
• Mentor junior researchers and contribute to the strategic direction of the Algorithmic Solutions Group.

• Stay abreast of state-of-the-art algorithms, and research advances beyond the state of the art in health sciences.

Qualifications:

Education:

• PhD. In Biomedical Engineering, health/biological sciences, or related areas.
• Domain knowledge and expertise in human physiology.

Experience:

• Extensive industry experience in designing, conducting, and leading digital biomarker research in at least one of the following areas: Neurology, Cardiology, Oncology and Metabolic, Respiratory or Renal Diseases.
• Proven experience in analyzing human physiological data to extract meaningful insights. 
• Proven experience in developing machine learning or signal