Faculty Member - Tenure-Track (Engineering Product Development)
Core
Define the next generation of human-aware, hardware-grounded AI systems and build a rigorous, externally funded research programme connecting deep generative modelling, physical reasoning, and robot learning.
Role type
Tenure-track Assistant Professor (Research & Teaching)
Builds
Externally funded research programmes, undergraduate and graduate courses, and a research group in physical AI and embodied systems.
Domain
Robotics, Computer Science, Machine Learning, Design Science
Deliverable
research
Required skills
Deep generative modelling, physical reasoning, human motion understanding, robot learning, 3D environment reasoning, safe robot learning, hierarchical planning, design-led engineering
Preferred skills
Egocentric synthetic data generation, predictive world models, physics-compliant motion synthesis, whole-body control, real-world system translation
Technologies
Generative AI, robotics frameworks, 3D modeling tools, simulation environments
Responsibilities
Establish an internationally recognized research group, secure competitive external research funding, publish in high-impact venues, teach undergraduate and graduate courses, supervise PhD and Master's students, collaborate with industry and public-sector partners
Seniority
Assistant Professor (Tenure-track)
