PhD Position in Collective Robot Learning

22.04.2022, Wissenschaftliches Personal

The Munich Institute of Robotics and Machine Intelligence (MIRMI) at the Technical University of Munich is looking for an outstanding applicant for a PhD position to conduct research in Collective Robot Learning and contribute to the KI.Fabrik (AI.Factory) project under the supervision of Prof. Sami Haddadin at the Chair of Robotics and Systems Intelligence (RSI).

About us

Located in the prosperous capital of Bavaria and home to over 39000 students, the Technical University of Munich (TUM) is one of the world’s top universities (top 4 European technical universities in The World University Ranking, top 50 in Shanghai Ranking, top 10 in Global University Employability Ranking, etc.). It is committed to excellence in research and teaching, interdisciplinary education, and the active promotion of promising young scientists. TUM benefits from the healthy mix of companies and startups of all sizes headquartered in the region and is tightly connected to regional research hospitals. The university also forges strong links with companies and scientific institutions across the world.

The TUM Munich Institute of Robotics and Machine Intelligence (MIRMI) is a globally visible interdisciplinary research center for machine intelligence, which is the integration of robotics, artificial intelligence and perception. Its three central innovation sectors are the future of health, the future of work, the future of the environment, and the future of mobility. More than 60 professors from various TUM faculties cooperate within the framework of MIRMI.

Description

The Munich Institute of Robotics and Machine Intelligence (MIRMI) at the Technical University of Munich is offering a PhD position focusing on using collective robot learning for tactile robots to learn manipulation skills to perform various tasks in future factory environments and beyond. We are seeking an outstanding applicant with passion for robotics and AI as well as a strong desire to shape the future AI-enabled, robotized factories.

The successful candidate will contribute to the AI.Factory project (https://www.mirmi.tum.de/mirmi/innovation-sectors/work/kifabrik/), which is a flagship project of the Bavaria High-tech Agenda to build the first prototype AI factory in Bavaria and enable research and development in cutting-edge technologies in robotics, telepresence, wearable electronics and AI to revolutionize the future of work in production.

This project will give you a unique opportunity to work with large scale networked robot systems to accelerate learning of robotic skills for manufacturing and logistics processes. You will work closely with researchers at MIRMI from various chairs and industry partners in an interdisciplinary environment to share expertise and collaborate on research publications in top conferences and journals in robotics and AI.

The goal of the first prototype of AI Factory is to show how state-of-the-art IT and mechatronic high-tech components (e.g., computer systems, sensors, mechatronic components, entertainment electronics) can be manufactured economically in Bavaria in the future, regardless of the number of production units. The AI Factory will be able to reconfigure its modular facilities and robots involved for different products and enable Production-as-a-Service. To achieve this, the successful applicant will work on open problems about autonomous learning of robotic skills, involving physical interaction with environments for challenging manipulation tasks, understanding and reasoning task sequences and collaborative AI for robotics. Knowledge and experience will be shared among the networked group of robots to accelerate learning and acquiring of work techniques.

Key responsibilities

• Contribute to the design and construction of reconfigurable and self-organized AI factory,
• Contribute to the design and implementation of networking mechanism of AI robots to enable knowledge transfer for collective learning,
• Collaborate with industry partners to generate analysis on skill primitives and taxonomy based on industrial use cases,
• Conduct research in autonomous skill learning using learning-from-demonstration / observation, reinforcement learning, genetic algorithms and or physics informed machine learning methods,
• Conduct research in collective robot learning to accelerate skill learning using large-scale networked AI robot systems.

Requirements

Please consider applying if you have a Master’s degree or equivalent in: electrical engineering, computer science, mechanical engineering, biomedical engineering, or a related field or equivalent practical experience. We especially seek individuals who have knowledge and expertise in the following areas:

• Strong programming skills (C/C++, Python, ROS, SQL)
• Knowledge and understanding of robot control, machine learning, optimization and planning
• Hands on experience with robots or conducting physical experiments on mechatronic systems
• Fluency in spoken and written English, German is a plus. Willingness to learn German is highly encouraged
• Good communication skills and ability to present complex content to a diverse audience
• High flexibility in acquiring new knowledge
• Creative and independent thinker
• Ability to work well in cross-functional and interdisciplinary teams with diverse people

Application

Interested applicants should send the following documents via email to [email protected] quoting “PhD Position in Collective Robot Learning” in the subject line.

• A motivation letter (1-3 pages) describing yourself, your research interests, qualifications, future career goals and research focus and why you would be a suitable candidate
• A detailed CV
• Academic transcripts from your Bachelor’s and Master’s degrees
• Email addresses of at least two references

The position will be filled as soon as possible and only shortlisted candidates will be notified. Preferences will be given to applications received before May 10, 2022.

TUM has been pursuing the strategic goal of substantially increasing the diversity of their staff. As an equal opportunity and affirmative action employer, both universities explicitly encourage nominations of and applications from women as well as from all others who would bring additional diversity dimensions to the university’s research and teaching strategies. Preference will be given to disabled candidates with equal qualifications. International candidates are highly encouraged to apply.

Technische Universität München
Munich Institute of Robotics and Machine Intelligence
Georg-Brauchle-Ring 60-62,
80992 München
[email protected]

Data Protection Information:
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Kontakt: [email protected]