Faculty Member - Tenure-Track (Engineering Product Development)

SUTD (Singapore University of Technology & Design); Singapore; On-site; SGD 90,000 - 160,000; Full time

Job summary

SUTD’s Engineering Product Development (EPD) Pillar invites applications for a full-time, tenure-track Assistant Professor in Human-Centric Embodied AI, Physical Intelligence, and World Models, at Singapore.

We seek candidates who advance predictive models for robots and embodied agents, bridging deep generative modeling with physical reasoning, motion understanding, and safe real-time control, contributing to design-led engineering.

Qualifications

• Evidence of research excellence and independence across disciplinary boundaries.
• Teaching experience and mentoring students at undergraduate/graduate levels.
• Credible plan for translation, collaboration, or impact with real-world systems.

Responsibilities

• Establish an internationally recognised research group and secure external funding.
• Publish in high‑impact venues and conferences.
• Teach undergraduate and graduate courses in robotics, AI, machine learning, or design‑led engineering.
• Supervise undergraduate, Master’s, and PhD students; contribute to project‑based education.
• Collaborate across EPD, other SUTD pillars, industry, and public‑sector partners.

Skills

Robot learning

Embodied AI

3D perception

Motion prediction

Planning & control

Safe robotics

Education

PhD in CS/Engineering/Robotics

Job description

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 Human-Centric Embodied AI, Physical Intelligence, and World Models.

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. We are particularly interested in candidates whose research develops predictive models that enable robots, intelligent products, and embodied agents to understand human intent, anticipate motion, reason about 3D 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.

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: systems that can sense, model, decide, and act in human-centred environments while respecting physical, safety, 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. Areas of particular interest include, but are not limited to, 3D digital humans and expressive body models; egocentric or first‑person embodied perception; synthetic data generation for embodied AI; human motion and intent prediction; action‑conditioned video or latent world models; physics‑compliant motion generation; whole‑body control; hierarchical planning for robots in human environments; safe robot learning; and the translation of generative models into reliable physical systems.

Candidate Profile

Strong applicants will demonstrate a clear research vision and a publication record in leading venues in robotics, computer vision, machine learning, graphics, human motion modelling, or related fields. The search is motivated by the calibre and direction of emerging scholars whose work spans egocentric synthetic data for embodied perception, predictive world models for realistic human motion, text‑conditioned and physics‑compliant motion synthesis, real‑world whole‑body control, and safe planning for robots operating in human‑centric environments. We are seeking candidates who can turn these advances into a coherent research agenda that is technically deep, externally visible, and well‑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, design of intelligent products, 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, industry, and public‑sector partners.

Qualifications

Applicants should have relevant expertise and experiencein Engineering, Computer Science, Robotics, Electrical Engineering, Applied Mathematics, Design, or a closely related field. 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 systems, and a credible plan for research translation, 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 contribution, self‑driving self‑??? Not mandatory? Not mandatory.