Faculty Member - Tenure-Track (Engineering Product Development)
The Engineering Product Development (EPD) Pillar at the Singapore University of Technology and Design (SUTD) invites applications for a full-time, tenure-track faculty position at the rank of Assistant Professor in the area of Healthcare Physical AI, Human-Centric Embodied Intelligence, and World Models for Health.
As generative AI moves from digital environments into the physical world, EPD seeks an exceptional scholar who can define the next generation of human-aware, hardware-grounded AI systems for healthcare. We are particularly interested in candidates whose research develops predictive models that enable medical robots, assistive devices, intelligent health products, and embodied agents to understand human intent, anticipate motion, reason about clinical and care environments, and act safely in real time. The successful candidate will build a rigorous and externally funded research programme that connects deep generative modelling, physical reasoning, human motion understanding, robot learning, and design-led engineering for healthcare applications.
Strategic Context. EPD is a multidisciplinary pillar focused on designing and building intelligent, technology-intensive products that work in the real world. The pillar brings together strengths in robotics, electronics, design science, systems and control, materials, healthcare engineering, manufacturing, and AI-enabled product development. This search is intended to strengthen EPD’s emerging capability in physical AI for healthcare: systems that can sense, model, decide, and act in clinical, rehabilitation, assistive, and home-care environments while respecting physical, safety, regulatory, and design constraints.
Research Areas of Interest. We welcome applicants working at the intersection of human-centric AI, embodied perception, generative world models, and robot control for healthcare. Areas of interest include patient-aware perception, human digital twins and expressive body models, synthetic data generation, human motion and intent prediction, physics-compliant motion generation, whole-body control, safe robot learning, hierarchical planning for healthcare environments, and the translation of generative models into reliable physical systems for clinical, rehabilitation, assistive, or home-care applications.
Candidate Profile. Strong applicants will demonstrate a clear research vision and a strong publication record in leading venues in robotics, computer vision, machine learning, healthcare engineering, graphics, human motion modelling, or related fields. We seek candidates whose work advances embodied healthcare perception, predictive world models, motion synthesis, whole-body control, and safe planning for robots in hospitals, rehabilitation, eldercare, and other human-centric healthcare settings. The ideal candidate will translate these advances into a coherent, technically rigorous, and externally visible research agenda aligned with SUTD’s design-centric mission.
Responsibilities. The successful candidate is expected to establish an internationally recognised research group; secure competitive external research funding; publish in high-impact venues; teach undergraduate and graduate courses in areas such as robotics, AI, machine learning, healthcare product design, sensing and control, or embodied systems; supervise undergraduate, Master’s, and PhD students; contribute to project-based and design-led education; and collaborate across EPD, other SUTD pillars, healthcare institutions, industry, and public-sector partners
Qualifications. Applicants should have relevant expertise in Engineering, Computer Science, Robotics, Electrical Engineering, Applied Mathematics, Design, Biomedical Engineering, or a closely related field by the appointment start date. They should show evidence of research excellence, independence, and the ability to work across disciplinary boundaries. Teaching experience, experience mentoring students, demonstrated engagement with real-world healthcare systems, and a credible plan for research translation, clinical collaboration, or impact will be viewed favourably
Why SUTD EPD. This position offers an opportunity to shape a distinctive research and education agenda in physical AI within a design-centric engineering environment. The successful candidate will join a pillar that values technical depth, hands-on creation, interdisciplinary collaboration, and human-centred innovation, and will contribute to preparing future engineers who can design intelligent products and systems for complex real-world settings.