Postdoctoral Scholar in AI and Digital Health Innovation

Do you want your AI research to move beyond benchmarks and make an impact in real-world healthcare? UCLA's Center for Advanced Surgical and Interventional Technology (CASIT) , part of the Department of Surgery at the David Geffen School of Medicine, is seeking a highly motivated Postdoctoral Scholar with strong expertise in computer vision, multimodal AI, machine learning, and/or agentic AI to help build the next generation of intelligent digital health solutions. You will work side by side with clinicians, engineers, researchers, and industry partners to transform multimodal health data- including wearable and sensor data, medical images and video, speech, human movement, physiological signals, and clinical information to create AI-powered tools for digital biomarkers, remote monitoring, precision health, clinical decision support, and intelligent surgical systems, with the ultimate goal of translating AI innovation into measurable improvements in patient care. About the Role: We are looking for a researcher with a Ph.D. in Computer Science, Biomedical Engineering, Electrical and Computer Engineering, Data Science, Robotics, Computational Health, or a closely related field and a strong record in AI, machine learning, digital health, or biomedical data science. You will lead interdisciplinary projects that apply advanced computational methods to clinically meaningful problems across the continuum of care—from early detection and functional assessment to intervention, surgery, recovery, and monitoring at home. Prior clinical experience is not required; scientific curiosity, strong quantitative skills, and a genuine interest in learning from clinicians and solving real-world healthcare problems are essential. What You Will Work On: Depending on your strengths and interests, projects may include: Digital biomarkers and multimodal health assessment: Develop AI models that integrate wearable sensors, movement, speech, physiological signals, imaging, video, and clinical data to characterize health status, frailty, resilience, cognitive-motor function, and disease progression. Wearables and remote monitoring: Transform longitudinal data from wearable and connected technologies into clinically actionable measures for monitoring patients in the hospital, at home, and in the community. Computer vision for healthcare: Apply computer vision to medical images, wound images, surgical video, and other visual health data for automated assessment, monitoring, prediction, and decision support. Agentic and generative AI for clinical care: Develop systems based on large language and vision-language models that reason across multimodal data, interact with tools, support clinical workflows, automate documentation, and enable personalized monitoring and care coordination. AI for brain and functional health: Combine speech, mobility, dual-task performance, wearable sensing, and clinical biomarkers to better characterize brain health, intrinsic capacity, and resilience to age- and disease-related decline. Intelligent surgical systems: Develop AI approaches for surgical video understanding, workflow analysis, skill assessment, robotic surgery, human-robot collaboration, and perioperative decision support. Digital interventions and precision health: Use data from telehealth, exercise, rehabilitation, and connected health programs to identify treatment response, engagement, and opportunities for personalized intervention. Key Responsibilities: Lead the design, development, and validation of AI and digital health research projects, from defining clinically meaningful questions to developing and evaluating working prototypes. Develop machine learning, deep learning, multimodal, computer vision, time-series, and/or foundation-model approaches for biomedical and clinical data. Build and curate multimodal datasets and analysis pipelines in compliance with IRB, HIPAA, and institutional requirements. Develop and validate digital biomarkers and AI-enabled decision-support tools with attention to reliability, generalizability, safety, and human oversight. Publish in leading AI, biomedical engineering, digital health, and clinical venues. Contribute to multidisciplinary grant proposals to federal agencies such as NIH, NSF, and ARPA-H, as well as industry-sponsored research. Mentor graduate and undergraduate trainees and collaborate closely with clinicians, engineers, researchers, and industry partners. Qualifications: Required Ph.D. in Computer Science, Biomedical Engineering, Electrical and Computer Engineering, Data Science, Robotics, Computational Health, or a related quantitative field, conferred by the start date. Strong research and publication record in AI, machine learning, computer vision, digital health, biomedical engineering, medical AI, or a closely related area. Expertise in one or more areas such as deep learning, computer vision, multimodal learning, time-series analysis, signal processing, foundation models, digital biomarkers, or agentic AI. Strong programming and data-analysis skills, particularly in Python and modern machine-learning frameworks such as PyTorch or equivalent. Experience working with complex, high-dimensional datasets. Clear scientific communication skills and a collaborative style suited to multidisciplinary research. Preferred Experience with wearable sensors, digital biomarkers, medical imaging, speech analytics, human movement, remote monitoring, or physiological signals. Experience with multimodal or longitudinal data, including fusion of video, sensor, audio, imaging, or clinical information. Knowledge of large language models, vision-language models, generative AI, or agentic AI methods such as tool use, planning, retrieval-augmented generation, or multi-agent systems. Experience with surgical or medical data, including surgical video, endoscopy, medical imaging, robotics, or perioperative datasets. Experience deploying models in real-world or real-time settings, including efficient inference or edge computing. Interest in trustworthy AI for healthcare, including uncertainty estimation, explainability, bias, privacy, safety, and human-AI interaction. Experience contributing to grant proposals, mentoring students, or translating research toward clinical validation. The posted UC Salary Scales set the minimum pay determined by rank and step at appointment. See Table 23: Postdoctoral Scholar-Employee, Postdoctoral Scholar-Fellow, Postdoctoral Scholar-Paid Direct, Fiscal Year. About Us: CASIT brings clinicians, engineers, data scientists, and researchers together to develop technologies that improve health across the continuum of care. Our work extends from AI-enabled surgical and interventional systems to wearable sensing, digital biomarkers, remote patient monitoring, speech and mobility analytics, wound monitoring, telehealth, healthy aging, and functional resilience. We are particularly interested in combining multimodal data to understand not only disease, but also function, recovery, resilience, and changes in health over time. Across all of our programs, the goal is the same: to move beyond proof-of-concept algorithms and develop technologies that can be clinically validated, deployed in real-world settings, and ultimately improve patient outcomes. Why Join Us? Direct Clinical Environment: Work within UCLA Health and the Department of Surgery, side by side with clinicians, and ground your research in meaningful real-world healthcare problems. Broad Digital Health Portfolio: Contribute to projects spanning AI, digital biomarkers, wearables, computer vision, remote monitoring, precision health, and intelligent surgical systems. Unique Multimodal Data: Work with combinations of speech, movement, wearable sensors, images, video, physiological signals, and clinical information. Translational Impact: Take projects beyond algorithm development toward prototypes, clinical validation, implementation, and real-world deployment. Mentorship and Leadership: Work under the direction of Dr. Bijan Najafi, Professor of Surgery and Research Director of CASIT, with opportunities to lead projects, mentor trainees, and develop an independent research program. Career Development: Build a strong profile for academic or industry careers through hands-on experience in scientific leadership, grant writing, multidisciplinary collaboration, and clinical translation. Joining our team offers a rare combination of cutting-edge AI research, digital health innovation, direct clinical exposure, and real-world translational impact. The shared values of the DGSOM are expressed in the Cultural North Star, which was developed by members of our community and affirms our unswerving commitment to doing what's right, making things better, and being kind. These are standards to which we hold ourselves, and one another. Please read more about this important DGSOM program. For additional information please contact: Bijan Najafi, Ph.D. Professor of Surgery & BioEngineering Research Director, Center for Advanced Surgical & Interventional Technology (CASIT) View email address on click.appcast.io. Ph.D. (or equivalent) in Computer Science, Biomedical Engineering, Electrical and Computer Engineering, Data Science, Robotics, Computational Health, or a related quantitative field #J-18808-Ljbffr University of California Los Angeles