Doctoral Candidate (DC 5) – 3D Perception in Dynamic Environments

21.10.2025, Wissenschaftliches Personal

About the ENGAGE Network

Mobile working machines (MWM) are critical to industries like construction, mining, and agriculture, and key to Europe’s sustainability and productivity goals. To meet rising demands for green, autonomous, and digital solutions, the ENGAGE network brings together top machine manufacturers (Volvo CE, Liebherr, Ponsse, AGCO), tech leaders (Bosch, Bosch Rexroth, Novatron, GIM Robotics), and six leading academic groups across Europe. ENGAGE will train a new generation of engineers through Industrial Doctorates, equipping them with cutting-edge expertise in AI, robotics, and mechanical engineering. Together, we’re building the future of smart, sustainable mobile machinery.

Position Overview

• Project Title: 3D Perception in Dynamic Environments
• Host Institution: Technical University of Munich (TUM), Germany – 12 months
• Industrial Partner: GIM Robotics, Finland – 24 months
• Supervisors: Prof. Achim Lilienthal (TUM), Dr. Jose Peralta (GIM Robotics)
• Target Degree: Doctoral Degree (PhD) awarded by the Technical University of Munich
• Starting Date: 1 March 2026 (negotiable)
• Contract Duration: 36 months, full-time employment
• Trial Period: 6 months

Project Tasks and Objectives

Industry Objectives:

1. Develop methods and algorithms for robust real-time 3D situational awareness and semantic 3D environmental segmentation.
2. Create algorithms and representations supporting multiple sensors (LiDAR, radar, camera) for dynamic environments like ports, airports, and logistics hubs.
3. Optimize algorithms for real-time operation on edge devices with limited computational resources.

Scientific Objectives:

1. Develop a system using foundation models to detect, classify, and track both stationary and moving objects from multimodal sensor data.
2. Integrate self-learning mechanisms for recognizing and adapting to unknown object types.
3. Incorporate language processing to interpret natural language input, infer motion characteristics, and refine object labels.
4. Develop introspection techniques to detect and mitigate system failures, such as model hallucinations.

The doctoral candidate will also contribute to outreach and dissemination via social media, project website, LinkedIn, YouTube, and blogs.

Eligibility and Requirements

We are seeking a talented, creative, and highly motivated researcher to join a multidisciplinary and innovative team at TUM and GIM Robotics.

Formal eligibility (MSCA rules):

• Applicants of any nationality may apply.
• Mobility rule: candidates must not have resided or carried out their main activity (work, study, etc.) in Germany for more than 12 months in the past 3 years.
• Candidates must be eligible for TUM’s Doctoral Program and must not already hold a doctoral degree.

Academic background:

• MSc in Industrial Engineering and Management, Robotics, Engineering, Systems Engineering, Automation, or related fields.
• Strong interest in engineering methods, perception systems, and robotics.

Additional requirements:

• Excellent written and spoken English (certificate may be required).
• Strong analytical and problem-solving skills.
• Ability to work both independently and collaboratively in international teams.
• Compliance with employer requirements in Germany and Finland.

Salary and Benefits

• 36-month full-time contract: 12 months at TUM (Germany) and 24 months at GIM Robotics (Finland).
• Salary and allowances per Marie Skłodowska-Curie Actions (MSCA) rules, including mobility and family allowances where applicable.
• Enrollment in TUM’s Doctoral Program with structured training, workshops, and networking.
• Access to both academic and industrial research environments supporting strong career development.

About the Host Institutions

Technical University of Munich (TUM), Germany
The Technical University of Munich (TUM) is one of Europe’s leading universities and a designated University of Excellence. Located in Munich, TUM ranks among the top technical universities worldwide. With more than 50,000 students and a thriving ecosystem of robotics research and startups, TUM provides an interdisciplinary environment with strong industrial links and a focus on innovation and sustainability.
https://www.tum.de/

Chair of Perception for Intelligent Systems (PercInS)
PercInS develops AI-driven perception systems for robots and intelligent platforms to act in complex, dynamic environments. Research areas include Perception for Intelligent Mobile Robots, Intelligent Robot Olfaction, Spatial Human-Robot Interaction, and AI Support Systems.
https://www.ce.cit.tum.de/pins

More about Munich and Germany:
muenchen.de | germany.travel | make-it-in-germany.com

GIM Robotics, Finland
GIM Robotics is a Finnish high-tech company developing intelligent mobile robotics solutions for logistics, construction, and heavy machinery sectors. Originating from Aalto University, it specializes in autonomous navigation, sensor fusion, and real-time 3D perception technologies.
https://gimrobotics.fi/

More about Finland:
visitfinland.com | infofinland.fi

Application Procedure

Application deadline: November 16, 2025 (23:59 EEST / UTC+2). Early applications are encouraged; interviews may start during the application period.

Required documents:

• Certified copies of Bachelor’s and Master’s degree certificates and transcripts (with Diploma Supplement, if applicable, in English).
• Curriculum Vitae (preferably Europass format).
• List of publications (if available, with indication of contributions).
• Motivation letter (max. 1 page) summarizing qualifications, research experience, and career goals.
• References: contact details of at least two referees (included in CV).
• Proof of residence: signed statement with supporting documents for residence over the past 3 years.

Please send your application as a single PDF to valeria.lopez-salazar@tum.de.

Contact

For further information, please contact:
Professor, Supervisor, Achim Lilienthal (TUM) – achim.j.lilienthal@tum.de
Valeria Salazar, Recruitment Coordinator – valeria.lopez-salazar@tum.de

Kontakt: achim.j.lilienthal@tum.de, valeria.lopez-salazar@tum.de