Doctoral Researcher in Humanoid Robotics, 3D Perception and Embodied AI

Doctoral Researcher in Humanoid Robotics, 3D Perception and Embodied AI

100%, Zurich

The Advanced Manufacturing Lab (am|z) at ETH Zurich, led by Prof. Markus Bambach, is seeking a highly motivated Doctoral Researcher to conduct research in humanoid robotics, 3D perception, and embodied artificial intelligence for autonomous manufacturing.

The position is embedded in an interdisciplinary research project aiming to enable humanoid robots to perceive, understand, and interact with complex manufacturing environments using novel RGB-D sensing technologies.

We are looking for a candidate with a strong background in robotics, computer vision, or machine learning who is passionate about developing intelligent robotic systems and translating scientific concepts into working solutions.

The successful candidate will investigate novel approaches to robot perception, simulation-to-real transfer, and autonomous manipulation, contributing to the development of intelligent humanoid systems capable of performing complex manufacturing tasks.

Project background

The Advanced Manufacturing Lab at ETH Zurich investigates advanced robotic technologies for flexible, intelligent, and autonomous manufacturing.

This Doctoral Researcher is part of a collaborative research project focused on developing intelligent humanoid robotic systems using next-generation, single-chip RGB-D sensing technologies.

The project aims to integrate novel depth-sensing hardware with advanced perception algorithms, simulation environments, and learning-based robotic control to enable autonomous and collaborative manufacturing operations.

Research activities span several interconnected areas:

• 3D simulation and synthetic data generation: Development of realistic manufacturing environments and simulation pipelines for generating annotated RGB-D data
• 3D semantic perception: Development of learning-based methods for object detection, segmentation, and scene understanding using RGB-D sensor information
• Sim-to-real transfer: Investigation of methods for transferring perception and manipulation capabilities from simulation to physical robotic systems
• Autonomous robotic manipulation: Integration of perception, planning, and control for robotic handling and assembly operations
• Collaborative humanoid robotics: Investigation of learning-based coordination strategies, including multi-agent reinforcement learning, for cooperative manufacturing tasks
• Language-guided robotic actions: Exploration of approaches that enable robots to interpret natural-language instructions and translate them into executable actions

The project combines fundamental research with experimental validation using physical humanoid robotic platforms and real manufacturing scenarios.

The doctoral research will focus on selected scientific challenges within these areas, with opportunities to contribute to the development of a fully integrated autonomous humanoid manufacturing demonstrator.

Job description

• Conduct independent scientific research in humanoid robotics, 3D perception, and learning-based robotic systems
• Develop and evaluate novel algorithms for RGB-D-based object detection, semantic segmentation, and 3D scene understanding
• Design and implement realistic robotic simulation environments and synthetic data generation pipelines for manufacturing applications
• Develop methods for improving the transfer of perception and manipulation capabilities from simulation to real-world robotic systems
• Design and implement data acquisition, annotation, processing, and evaluation workflows for synthetic and real RGB-D datasets
• Integrate perception algorithms with robotic manipulation, motion planning, and control frameworks
• Investigate learning-based approaches to autonomous robotic decision-making, with opportunities to explore multi-agent coordination and language-guided manipulation
• Implement, test, and validate developed methods on physical robotic and humanoid platforms
• Plan and conduct scientific experiments, establish quantitative benchmarks, and systematically evaluate the performance of developed methods
• Develop reproducible research software and contribute to shared software frameworks and experimental infrastructure
• Publish research findings in leading international robotics, computer vision, and machine learning conferences and journals
• Collaborate with researchers and industrial partners involved in the project and contribute to the supervision of student research projects

Profile

We are looking for a highly motivated and independent researcher with strong analytical and programming skills, scientific curiosity, and a passion for intelligent robotic systems.

You should have:

• A Master's degree in Robotics, Computer Science, Mechanical Engineering, Electrical Engineering, Artificial Intelligence, or a closely related field
• A strong foundation in robotics, computer vision, machine learning, or related computational methods
• Excellent programming skills, particularly in Python and preferably also C++
• Experience with machine learning frameworks, such as PyTorch, and the development, training, or evaluation of learning-based models
• A solid understanding of robotics fundamentals, including coordinate transformations, kinematics, motion planning, or robotic manipulation
• Practical experience in at least one relevant area, such as 3D computer vision, robotic perception, robotics simulation, or robot learning
• Experience with scientific experimentation, quantitative evaluation, and the analysis of experimental results
• Familiarity with Linux-based development environments, Git, and collaborative software development practices
• The ability to independently investigate challenging research questions, develop new ideas, and systematically evaluate potential solutions
• A strong motivation to pursue doctoral research and contribute to scientific publications
• Fluent English, both written and spoken
• Knowledge of Korean and/or German is an advantage

The following qualifications would be an advantage:

• Experience with RGB-D cameras, depth sensing, point clouds, 3D reconstruction, or semantic scene understanding
• Familiarity with robotics frameworks such as ROS/ROS 2
• Experience with robotics simulation platforms such as NVIDIA Isaac Sim, MuJoCo, Gazebo, or similar environments
• Experience with synthetic data generation, dataset annotation, or simulation-to-real transfer
• Knowledge of reinforcement learning, imitation learning, or learning-based robotic manipulation
• Familiarity with vision-language models (VLMs), large language models (LLMs), or language-conditioned robotic policies
• Experience with multi-robot systems, humanoid robotics, or collaborative manipulation
• Hands-on experience integrating sensors, programming robots, or conducting experiments on physical robotic platforms
• Familiarity with Docker, automated testing, CI/CD pipelines, or reproducible machine learning workflows
• Previous research experience demonstrated through a Master's thesis, research projects, publications, or contributions to scientific conferences

We particularly encourage applications from candidates who combine strong theoretical foundations with practical programming skills and an interest in validating their research on real robotic systems.

We offer

• You will join an interdisciplinary research environment combining robotics, artificial intelligence, computer vision, and advanced manufacturing
• The opportunity to pursue a Doctorate at ETH Zurich within a collaborative international research project, subject to fulfilment of ETH Zurich's doctoral admission requirements
• The opportunity to conduct original scientific research at the intersection of humanoid robotics, embodied AI, 3D perception, and autonomous manufacturing
• A high degree of scientific independence, with opportunities to develop research ideas, investigate novel methods, and shape the direction of your doctoral research
• Access to robotic research infrastructure, including physical robotic platforms, sensing technologies, and experimental manufacturing environments
• Close collaboration with researchers from complementary scientific disciplines and industrial partners developing advanced sensing and robotic technologies
• Opportunities to publish in leading international conferences and journals and participate in the international robotics research community
• A stimulating academic environment at ETH Zurich, with opportunities for scientific exchange, professional development, and collaboration

We value diversity and sustainability

In line with our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish. Sustainability is a core value for us – we are consistently working towards a climate-neutral future.

Curious? So are we.

We look forward to receiving your online application with the following documents:

• Curriculum vitae (CV)
• Motivation letter describing your research interests, relevant experience, and motivation to pursue a Doctorate in humanoid robotics, 3D perception, or embodied AI
• Academic transcripts and degree certificates
• Master's thesis or a summary of relevant previous research work

Optional but encouraged:

• Portfolio, GitHub repository, project videos, or examples of previous robotics, computer vision, or machine learning projects
• Scientific publications, conference papers, research reports, or other examples of academic contributions

Further information about the Advanced Manufacturing Lab can be found on our website. Questions regarding the position should be directed to Dr. Jan Petrik, jpetrik@ethz.ch (no applications).

Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.

We would like to point out that the pre-selection is carried out by the responsible recruiters and not by artificial intelligence.

About ETH Zürich

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