PhD and Postdoctoral Positions in "Robot motion and control algorithms for soft material handling”

30.05.2025, Wissenschaftliches Personal

We are seeking highly qualified and motivated individuals 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 positions focus 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

These positions are 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

PhD Position:

• Master’s degree in Robotics, Mechanical Engineering, Electrical Engineering, Computer Engineering, Computer Science, or a closely related field
• Strong background in robotics fundamentals: kinematics, dynamics, control, planning
• Proficiency in programming (C++, Python), and experience with ROS
• Experience with simulation tools such as MuJoCo, Gazebo
• Prior exposure to machine learning and perception systems is an advantage
• Excellent communication skills and proficiency in English
  
  

Postdoctoral Position:

• 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
• 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 with the German public service salary scale (TV-L)
  
  

Application Process

Interested applicants should upload their application including the following documents

1. curriculum Vitae, including contact details of at least two academic references
2. academic transcripts (Bachelor’s and Master’s degrees for PhD applicants; also PhD certificate for Postdoc applicants)
3. two to three representative publications or writing samples (e.g., Master’s thesis, conference papers)

to the following link here quoting " 65MIRMIPhD/Postdoc ” in the subject line. The r eview of applications will begin immediately and continue until the positions are filled. Preference will be given to applications received before June 30, 2025. Only shortlisted candidates will be contacted.

TUM has been pursuing the strategic goal of substantially increasing the diversity of its staff. As an equal opportunity and affirmative action employer, TUM explicitly encourages 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.

Contact Information

Dr. Hamid Sadeghian: hamid.sadeghian@tum.de

Kontakt: hamid.sadeghian@tum.de