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ETH Zurich

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

Degree Level

PhD

Field of study

Computer Science

Funding

Doctoral position at ETH Zurich; funding details such as stipend amount are not specified in the post. The role is a paid doctoral researcher opening within a collaborative international research project, subject to ETH Zurich doctoral admission requirements.

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Country

Switzerland

University

ETH Zurich

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Keywords

Computer Science
Mechanical Engineering
Electrical Engineering
Computer Vision
Semantic Segmentation
Robotics
ML

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About this position

ETH Zurich’s Advanced Manufacturing Lab (am|z), led by Prof. Markus Bambach, is recruiting a Doctoral Researcher in humanoid robotics, 3D perception, and embodied AI for autonomous manufacturing.

The project focuses on enabling humanoid robots to perceive, understand, and interact with complex manufacturing environments using novel RGB-D sensing technologies. Research topics include robot perception, semantic segmentation, 3D scene understanding, simulation-to-real transfer, autonomous manipulation, multi-agent reinforcement learning, and language-guided robotic actions.

The position is ideal for candidates with a strong background in robotics, computer vision, machine learning, or related computational methods, plus strong programming skills in Python (and preferably C++). Experience with PyTorch, ROS/ROS 2, robotics simulation, RGB-D cameras, point clouds, synthetic data generation, or robot learning is especially relevant.

The doctoral researcher will conduct independent research, develop and evaluate algorithms, build simulation and data pipelines, integrate perception with manipulation and control, and validate methods on physical robotic and humanoid platforms. The role also includes publishing in leading robotics, computer vision, and machine learning venues and collaborating with academic and industrial partners.

Applicants should hold a Master’s degree in a relevant field and be fluent in English. Korean and/or German are an advantage. ETH Zurich notes that doctoral admission requirements must be met.

Applications are submitted online only. Required documents include a CV, motivation letter, transcripts and degree certificates, and a Master’s thesis or summary of prior research. Optional materials such as a GitHub portfolio, project videos, or publications are encouraged.

Funding details

Doctoral position at ETH Zurich; funding details such as stipend amount are not specified in the post. The role is a paid doctoral researcher opening within a collaborative international research project, subject to ETH Zurich doctoral admission requirements.

What's required

Applicants should have a Master's degree in Robotics, Computer Science, Mechanical Engineering, Electrical Engineering, Artificial Intelligence, or a closely related field. Strong background in robotics, computer vision, machine learning, or related computational methods is required, along with excellent programming skills in Python and preferably C++. Experience with PyTorch or similar ML frameworks, robotics fundamentals (coordinate transformations, kinematics, motion planning, manipulation), and practical experience in 3D computer vision, robotic perception, simulation, or robot learning are expected. Candidates should also have experience with scientific experimentation and quantitative evaluation, be comfortable with Linux, Git, and collaborative software development, and be fluent in English. Korean and/or German are advantageous, as are experience with RGB-D cameras, ROS/ROS 2, simulation platforms, synthetic data, sim-to-real transfer, reinforcement learning, VLMs/LLMs, multi-robot systems, or prior research output.

How to apply

Apply online through ETH Zurich’s application portal only. Prepare a CV, motivation letter, academic transcripts and degree certificates, and your Master's thesis or a summary of relevant research work. Optional supporting materials such as a portfolio, GitHub, project videos, or publications are encouraged.

More information can be found here

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