人形机器人3D感知与具身智能博士生

Doctoral Researcher in Humanoid Robotics, 3D Perception and Embodied AI
原始招聘页面

研发人形机器人RGB-D感知与具身智能算法

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形式资格 0.00
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评分理由
The candidate profile is blank, so there is no evidence of the required Master's degree, robotics/computer vision/ML skills, or methodological transferability. Without candidate data, the interview probability is effectively zero rather than a positive shortlist estimate. · 迁移评估:Not assessable - no candidate profile supplied
机构
ETH Zurich
地点
Zürich · CH
类型
博士生
截止
—
资助
funded
来源
🎓 ETH Zurich
软性注意
  • 具备韩语和/或德语知识是加分项(非硬性要求)
  • 编程技能除 Python 外,最好也掌握 C++
  • 优先有真实机器人平台实操经验者
  • 优先有 ROS/ROS 2、Isaac Sim/MuJoCo/Gazebo 等仿真平台经验者
  • 优先有 RGB-D 相机、点云、3D 重建、语义场景理解经验者
  • 优先有强化学习/模仿学习/视觉语言模型相关经验者
数据完整(5/5),可生成高质量材料
PI 信息
主导师 Markus� Bambach 直接提取
身份 已确认 A5005535794
院系 Advanced Manufacturing Lab (am|z), ETH Zurich
联系邮箱 jpetrik@ethz.ch
在 OpenAlex 手动核查
PI 近期论文(9 篇)
标记为「重要」或「很重要」的论文会进入 MV/CV 生成上下文;「一般」和「忽略」不进入。每次生成都读取最新标记。
[2026] Point cloud registration for non-destructive, high-resolution coating thickness measurement from 3D scans 通讯作者
Simon Duenser · ... · Markus� Bambach
[2026] Microstructure engineering of Ti-6Al-4V in laser powder bed fusion via 1D thermal modeling and supporting experiments 通讯作者
Carina van der Linde · ... · Markus� Bambach
[2026] Condition-Robust Tool Remaining Useful Life Prediction under Highly Variable Milling Conditions 通讯作者
Stefania Ferrisi · ... · Markus� Bambach
[2026] Near-net-shaped manufacturing of complex-shaped metallic components using selective powder deposition and spark plasma sintering 通讯作者
Marco Bernet · ... · Markus� Bambach
[2026] 激光制造中瞬态熔池的基本稳定极限与可控性 通讯作者
Fundamental stabilization limits and controllability of transient melt pools in laser-based manufacturing
Yunong Lin · ... · Markus� Bambach
[2026] 双曲平衡律反馈控制的贝叶斯方法 第一作者
A Bayesian approach to feedback control for hyperbolic balance laws
Markus� Bambach · ... · Yunong Lin
[2026] An integrated experimental and modeling approach to mitigate defects in multi-layer bronze HSLC 通讯作者
Francesco Rippa · ... · Markus� Bambach
[2026] “基于置信度减少 通讯作者
Corrigendum to “Reducing thermal errors with confidence: Uncertainty-based compensation for precision machine tools” [CIRP J Manuf Sci Technol 61 (2025) 400–409]
Petr Kaftan · ... · Markus� Bambach
[2026] Microstructure engineering of Ti-6Al-4V in laser powder bed fusion via 1D thermal modeling and supporting experiments 通讯作者
Carina van der Linde · ... · Markus� Bambach
手动添加论文 DOI
职位描述 / 要求

职位描述

100%, Zurich print 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. Workplace Workplace 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 chevron_right Working, teaching and research at ETH Zurich 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 ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow. 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. Apply online now About ETH Zürich ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow. Let’s connect

职位要求

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.

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