RAI Institute
Sr. Research Scientist - Physically-Grounded World Modeling
RAI Institute, Cambridge, Massachusetts, us, 02140
Our Mission
Our mission is to solve the most important and fundamental challenges in AI and Robotics to enable future generations of intelligent machines that will help us all live better lives.
Our research group, a part of the RAI institute's Perception team, is dedicated to building the next generation of intelligent scene models. We focus on creating representations that are deeply grounded in the physics of the real world. We operate in a dynamic environment, translating research breakthroughs into demonstrable progress in physical intelligence. Our work exists at the intersection of two critical challenges:
Analysis (Understanding the Now) Deconstructing scenes into their fundamental components including 3D geometry, semantics, physical properties (like friction and mass), and dynamics (like articulation and forces).
Synthesis (What Happens Next?) Using this understanding to power generative world models, hybrid physics engines, and differentiable simulators that can predict how a scene will evolve over time, conditioned on agent actions.
What You Will Do
Research, design, and implement novel algorithms for understanding and modeling complex 3D scenes, with a focus on integrating geometry, semantics, and physics
Develop and advance generative and physics-informed models capable of predicting realistic future states and dynamic interactions for applications like robotic manipulation
Design and curate large-scale datasets to enhance model capabilities in physically-grounded and specialized applications
Create robust 3D representations that capture not just object appearance, but also physical properties, affordances, and causal dynamics
Incorporate principled uncertainty estimation into your models to ensure they are reliable and aware of their own limitations
Collaborate with a multidisciplinary team of researchers and engineers to integrate your work into larger systems and build compelling demonstrations
Share your innovative work with the community through publications at top-tier conferences (e.g., CoRL, CVPR, NeurIPS)
Mentor junior researchers and engineers, fostering a culture of technical excellence and collaborative innovation
What We Are Looking For
A PhD, or MS with equivalent research experience in Computer Science, Robotics, or a related field
5+ years of relevant post-graduate research or industry experience in robotics, computer vision, computer graphics, or machine learning
Strong programming skills in Python and/or C++ and deep experience with a major deep learning framework (e.g., PyTorch).
Experience applying research to robotic systems (e.g., using ROS 2, integrating models on physical hardware).
A proven track record of creativity and research excellence, demonstrated by publications in leading ML and Robotics conferences.
Deep expertise in one or more of the following areas: (1). 3D Scene Understanding: (e.g., NeRFs, 3D Gaussian Splatting, 3D reconstruction, geometric deep learning). (2). Generative Modeling: (e.g., Diffusion Models, VAEs, LLMs, Multimodal Models) applied to 3D or dynamic data. (3). Physics-Informed AI: (e.g., Differentiable simulation, Physics-based modeling, System identification).
Bonus Qualifications
Experience with
large-scale model training , including distributed training techniques
Familiarity with MLOps workflows and tools (e.g., Docker, cloud computing) for large-scale experiments
Familiarity with causal representation learning or related techniques.
Why Join Us We offer a unique environment for those who want to do foundational work with real-world impact, without the constraints of a product-driven roadmap.
Intellectual Freedom:
The latitude to pursue ambitious, long-term research goals in a culture that prioritizes scientific discovery
Unparalleled Resources:
Access to extensive GPU compute clusters, unique proprietary datasets, and a world-class robotics lab featuring a variety of commercial and
in‑house custom robotic platforms.
A Culture of Balance:
We believe groundbreaking work happens when people have the time to think deeply. We offer a more relaxed, collaborative atmosphere with a genuine commitment to work‑life balance.
A Full‑Stack Team:
You'll be surrounded by, and learn from, world‑class experts across the entire robotics stack—from custom hardware design and embedded systems to ML engineering, computer vision, and AI theory.
We provide equal employment opportunities to all employees and applicants for employment and prohibit discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other
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Our research group, a part of the RAI institute's Perception team, is dedicated to building the next generation of intelligent scene models. We focus on creating representations that are deeply grounded in the physics of the real world. We operate in a dynamic environment, translating research breakthroughs into demonstrable progress in physical intelligence. Our work exists at the intersection of two critical challenges:
Analysis (Understanding the Now) Deconstructing scenes into their fundamental components including 3D geometry, semantics, physical properties (like friction and mass), and dynamics (like articulation and forces).
Synthesis (What Happens Next?) Using this understanding to power generative world models, hybrid physics engines, and differentiable simulators that can predict how a scene will evolve over time, conditioned on agent actions.
What You Will Do
Research, design, and implement novel algorithms for understanding and modeling complex 3D scenes, with a focus on integrating geometry, semantics, and physics
Develop and advance generative and physics-informed models capable of predicting realistic future states and dynamic interactions for applications like robotic manipulation
Design and curate large-scale datasets to enhance model capabilities in physically-grounded and specialized applications
Create robust 3D representations that capture not just object appearance, but also physical properties, affordances, and causal dynamics
Incorporate principled uncertainty estimation into your models to ensure they are reliable and aware of their own limitations
Collaborate with a multidisciplinary team of researchers and engineers to integrate your work into larger systems and build compelling demonstrations
Share your innovative work with the community through publications at top-tier conferences (e.g., CoRL, CVPR, NeurIPS)
Mentor junior researchers and engineers, fostering a culture of technical excellence and collaborative innovation
What We Are Looking For
A PhD, or MS with equivalent research experience in Computer Science, Robotics, or a related field
5+ years of relevant post-graduate research or industry experience in robotics, computer vision, computer graphics, or machine learning
Strong programming skills in Python and/or C++ and deep experience with a major deep learning framework (e.g., PyTorch).
Experience applying research to robotic systems (e.g., using ROS 2, integrating models on physical hardware).
A proven track record of creativity and research excellence, demonstrated by publications in leading ML and Robotics conferences.
Deep expertise in one or more of the following areas: (1). 3D Scene Understanding: (e.g., NeRFs, 3D Gaussian Splatting, 3D reconstruction, geometric deep learning). (2). Generative Modeling: (e.g., Diffusion Models, VAEs, LLMs, Multimodal Models) applied to 3D or dynamic data. (3). Physics-Informed AI: (e.g., Differentiable simulation, Physics-based modeling, System identification).
Bonus Qualifications
Experience with
large-scale model training , including distributed training techniques
Familiarity with MLOps workflows and tools (e.g., Docker, cloud computing) for large-scale experiments
Familiarity with causal representation learning or related techniques.
Why Join Us We offer a unique environment for those who want to do foundational work with real-world impact, without the constraints of a product-driven roadmap.
Intellectual Freedom:
The latitude to pursue ambitious, long-term research goals in a culture that prioritizes scientific discovery
Unparalleled Resources:
Access to extensive GPU compute clusters, unique proprietary datasets, and a world-class robotics lab featuring a variety of commercial and
in‑house custom robotic platforms.
A Culture of Balance:
We believe groundbreaking work happens when people have the time to think deeply. We offer a more relaxed, collaborative atmosphere with a genuine commitment to work‑life balance.
A Full‑Stack Team:
You'll be surrounded by, and learn from, world‑class experts across the entire robotics stack—from custom hardware design and embedded systems to ML engineering, computer vision, and AI theory.
We provide equal employment opportunities to all employees and applicants for employment and prohibit discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other
#J-18808-Ljbffr