Tenure-track Assistant Professor in AI World Models for Embodied Systems

The Ohio State University; Columbus (OH); On-site; USD 90,000 - 140,000; Full time

Job summary

The Ohio State University in Columbus, OH seeks a tenure-track Assistant Professor to advance AI world models for embodied systems. The position anchors in the Department of Computer Science and Engineering (70%), with a joint appointment in one embodied systems unit.

Start as early as Fall 2027 on the Columbus campus. Responsibilities include leading world-model research, mentoring students, and developing curricula, while pursuing external funding and fostering collaborations across campus and

Qualifications

• PhD completed by start date.
• Strong record of research in world models and related areas such as embodied AI, robot learning, computer vision, multimodal models.

Responsibilities

• Lead or co-lead a research program in foundational world-model methods and predictive models.
• Collaborate across Engineering units and campus living labs.
• Mentor PhD, MS, and undergraduates with emphasis on inclusive participation.
• Contribute to blended AI/engineering curriculum for graduate and undergraduate programs.
• Pursue external funding from NSF, DOE, industry, and partners.
• Engage with campus, industry, and government stakeholders for research impact.

Skills

World-model research

Embodied AI

Multimodal perception

Physics-grounded AI

External funding

Mentorship

Interdisciplinary collaboration

Education

PhD in Computer Science or Computer Engineering

Tools

Differentiable simulation

Digital twins

Computer graphics

Job description

Tenure-track Assistant Professor in AI World Models for Embodied Systems

The Ohio State University

Columbus, OH

Position Overview

The College of Engineering at The Ohio State University invites applications for a tenure-track faculty position at the rank of Assistant Professor. We seek candidates who advance the computational foundations of AI world models: models that inherently learn general representations of physical environments, predict how those environments evolve, and reason about the consequences of actions. The goal would be to exploit world models to close the gap between simulation-trained AI and dependable real-world autonomy. Relevant research would leverage multimodal and spatiotemporal learning, context-informed and knowledge (e.g., physics)-grounded AI, generative and predictive modeling, learned simulation models and digital twins, and embodied or agentic AI. Representative grand-challenge application drivers for candidates’ research would include water resource management, infrastructure inspection, swarm operations, adaptive traffic and pedestrian flow management for next-generation urban mobility, robotics, and mobility based on agentic, autonomous, cooperative, resilient, and secure AI platforms.

The position will be anchored in the Department of Computer Science and Engineering (70%), with a joint appointment (30%) determined by the candidate’s expertise and interest in one of three units with embodied systems: the Department of Civil, Environmental, and Geodetic Engineering, the Knowlton School of Architecture, or the Department of Mechanical and Aerospace Engineering. This position is located on the main Columbus campus of The Ohio State University and starts as early as Fall 2027.

Performance Objectives

• Lead or co-lead a research program in foundational world-model methods, including domain-grounded data generation, multimodal perception, physics-grounded predictive models, or learned simulation and digital twins.
• Collaborate across Engineering units and campus living labs.
• Mentor PhD, MS, and undergraduate students, with attention to broadening participation in embodied AI and robotics.
• Contribute to potentially blended curriculum development that enriches traditional offerings in AI and engineering at the graduate and undergraduate levels.
• Pursue external funding to sustain and grow the research program, including continued NSF, DOE, DOT, and industry support.
• Engage with campus, industry, and government stakeholders (facilities, transportation, public safety) as an integral part of the research.

Education and Experience Requirements

Required:

• PhD in Computer Science, Computer Engineering, or a related field of Engineering, Physics, or Applied Mathematics, completed by the position start date.
• A strong record of research in world models and related areas such as embodied AI, robot learning, computer vision, multimodal models integrating vision, language, geometry, sensor streams, and/or engineering data, 3D/4D scene understanding, reasoning, planning, physics-grounded AI, or simulation-based learning.
• Demonstrated ability (or clear potential, for junior candidates) to secure competitive external research funding.
• Commitment to graduate and undergraduate teaching and mentorship.
• Experience with multimodal sensing, 3D/4D representations, multi-robot systems, or aerial and ground platforms.
• Experience with physics-informed, causal, or hybrid physics-AI models.
• Background in learned simulators, differentiable simulation, digital twins, computer graphics, or physical simulation.
• Experience with uncertainty, robustness, and generalization in open, changing, or partially observed physical environments.
• Visionary Mindset: The ability to articulate a clear research agenda that addresses fundamental challenges in current AI models, such as reasoning, generalization, and robustness.
• Evidence of research excellence in mathematical and theoretical frameworks in computing.
• Leadership qualities and vision for contributing to a nationally recognized research center.
• Experience with developing new courses and degree programs.
• A commitment to interdisciplinary education and collaborative research.
• A track record of interdisciplinary collaboration.

Equal Opportunity Statement

The university is an equal opportunity employer, including veterans and disability.