Postdoctoral Position in “Robot motion and control algorithms for deformable objects manipulation”, Munich Institute of Robotics and Machine Intelligence (MIRMI), Technical University of Munich – Garmisch-Partenkirchen Campus
We are seeking an outstanding candidate for a Postdoctoral position in the field of robot motion and control algorithms for soft material handling, starting immediately. We are looking for a highly qualified and motivated individual with a strong academic background in robotics and a keen interest in advancing the frontiers of deformable object manipulation. Ideal candidates are those aiming for a long-term research career in academia or industry.
About us
Located in the prosperous capital of Bavaria and home to over 50000 students, the Technical University of Munich (TUM) is one of the world’s top universities (top 3 European technical universities in THE World University Ranking, top 50 in Shanghai Ranking, top 10 in Global University Employability Ranking, etc.) and home to one of the most vibrant environments in robotics research, industry and startups. 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 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. 70 professors from various TUM faculties cooperate within the framework of MIRMI.
Position Overview
Join a highly interdisciplinary and innovative team at MIRMI to conduct cutting-edge research in robotic manipulation of deformable objects. The position focuses on motion planning and control of 1D and 2D deformable objects (e.g., cables, cloth) through bimanual and adaptive robotic strategies.
The work will involve the integration of:
- Advanced motion planning and control algorithms
- Multi-modal perception techniques (e.g., vision, tactile, force)
- Machine learning models for physical behavior prediction and manipulation strategy adaptation
- Real-world robotic systems, including dual-arm manipulators and soft robotic grippers
The position is part of broader strategic efforts to enable intelligent robot systems capable of handling soft, flexible, and deformable materials in unstructured environments, with applications in industry, healthcare and domestic robotics.
Key Research Topics
- Robotic manipulation of deformable linear (e.g., cables) and surface objects (e.g., fabrics)
- Bimanual coordination and manipulation planning
- Vision- and tactile-based perception and state estimation of deformable objects
- Simulation and reality gap bridging for deformable object interaction (using environments such as MuJoCo, PyBullet, or NVIDIA Isaac Sim)
- Adaptive feedback control using learned and analytical models
- Physics-informed machine learning for deformation modeling and prediction
- Integration of perception, planning, and control for robust real-time robotic performance
Requirements
- Ph.D. in Robotics, Mechanical Engineering, Electrical Engineering, or a closely related field
- Proven research experience and publication track record in robotic manipulation, deformable object handling, or related domains
- Hands-on experience with robotic hardware (e.g., robot arms, tactile sensors)
- Familiarity with model-based planning approaches, robot force/motion control, and reinforcement learning
- Proficiency in programming (C++, Python), and experience with ROS
- Experience with simulation tools such as MuJoCo, Gazebo
- Strong project management and mentoring skills
- Excellent command of English; German is a plus but not required
What We Offer
- A highly dynamic and interdisciplinary research environment at one of Europe’s top technical universities
- Access to state-of-the-art robotics labs and collaborative projects with leading industrial partners
- Opportunities to publish in top-tier conferences and journals (e.g., ICRA, RSS, IJRR)
- Active participation in European robotics and AI research initiatives
- Support for personal and professional development, including teaching, supervision, and leadership roles
- Competitive compensation in line Collective Agreement for the Civil Service of the Länder (TV-L).
TUM strives to raise the proportion of women in its workforce and explicitly encourages applications from qualified women. The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally equivalent suitability, aptitude and professional performance. International applicants are strongly encouraged to apply.
Application Process
We look forward to receiving your comprehensive application documents.
Please upload them using the subject line “73MIRMIPostdoc GAP” via the following link: here .
The review of applications will begin immediately and continue until the position is filled. Preference will be given to applications received by January 15, 2026. Only shortlisted candidates will be contacted.
Data Protection Information:
When you apply for a position with the Technical University of Munich (TUM), you are submitting personal information. With regard to personal information, please take note of the Datenschutzhinweise gemäß Art. 13 Datenschutz-Grundverordnung (DSGVO) zur Erhebung und Verarbeitung von personenbezogenen Daten im Rahmen Ihrer Bewerbung. (data protection information on collecting and processing personal data contained in your application in accordance with Art. 13 of the General Data Protection Regulation (GDPR)). By submitting your application, you confirm that you have acknowledged the above data protection information of TUM.
Kontakt: Dr. Hamid Sadeghian: hamid.sadeghian@tum.de
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