Marie Skłodowska-Curie Industrial Doctorate (ENGAGE Network)
Doctoral Candidate (DC 3) – As-built model updating using sensor data for an automatic documenting of a worksite
21.10.2025, Wissenschaftliches Personal
We are looking for a Doctoral Candidate (DC 3) to work on as-built model updating using sensor data for automatic documentation of a worksite within the Marie Skłodowska-Curie Industrial Doctorate (ENGAGE Network).
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: As-built Model Updating Using Sensor Data for Automatic Worksite Documentation
- Host Institution: Technical University of Munich (TUM), Germany – 12 months
- Industrial Partner: Novatron, Finland – 24 months
- Supervisors: Prof. Achim Lilienthal (TUM), Antti Kolu (Novatron)
- Target 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
Objectives
Industry:
- Object detection on construction sites to verify elements of a BIM (Building Information Modelling) model.
- Updating BIM model information based on sensor data and object detection.
- 3D object measurement system for construction sites.
- Machine task identification by using a BIM model and data collected with mobile work machines.
Science:
- Development of a multi-layer, semantic (MLS) mapping pipeline for changing environments as input to a BIM model.
- Evaluation of introspective consistency and correlation across layers in the MLS map as further input to the BIM model.
- Development of methods for automatic or semi-automatic MLS and BIM model updates with minimal input from human operators.
- Evaluation of variable density mapping approaches that adapt to the information density required for BIM models.
Eligibility and Requirements
We are seeking a talented, creative, and highly motivated researcher to join a multidisciplinary and innovative team at the Technical University of Munich (TUM) and Novatron.
Formal eligibility (MSCA rules):
- Applicants of any nationality are welcome.
- At the time of recruitment, the researcher must not have resided or carried out main activity in Germany for more than 12 months in the 3 years prior.
- Candidates must be eligible for enrollment in the Doctoral Program at TUM and must not already hold a doctoral degree.
Academic background:
- Master of Science (MSc) in Industrial Engineering and Management, Robotics, Engineering, specializing in Systems Engineering, Automation, or related subjects.
- Strong interest in robotics and perception-driven automation.
Additional requirements:
- Proficiency in written and spoken English (certificate may be requested).
- Strong analytical and problem-solving skills.
- Ability to work independently and collaboratively in an international, interdisciplinary environment.
- Compliance with the respective employers' requirements in Germany and Finland.
Salary and Benefits
- 36-month full-time contract (12 months at TUM, Germany, 24 months at Novatron, Finland).
- Salary and allowances per Marie Skłodowska-Curie Actions (MSCA) funding rules, including mobility and family allowances.
- Enrollment in TUM’s Doctoral Program with structured training, workshops, and networking opportunities.
- Access to both academic and industrial research environments, enabling strong career development opportunities.
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, Bavaria, TUM ranks among the top technical universities worldwide. With over 50,000 students and a vibrant ecosystem of robotics research, industry, and startups, TUM offers a dynamic and interdisciplinary environment for doctoral candidates.
Chair Perception for Intelligent Systems at TUM
The chair Perception for Intelligent Systems (PercInS) investigates novel methods and technologies for robotic platforms and other intelligent systems to perceive and act in unconstrained, dynamic environments.
https://www.ce.cit.tum.de/pins
More about Munich and Germany:
- https://www.muenchen.de/int/en.html
- https://www.germany.travel/en/home.html
- https://www.make-it-in-germany.com/en/
Novatron, Finland
Novatron is a Finnish leader in digital machine control systems for earthmoving and construction machinery. It develops advanced machine control systems, software, and cloud services. Novatron employs around 130 professionals, including 60 engineers and scientists in R&D.
More about Tampere and Finland:
Application Procedure
Application deadline: November 16, 2025 (23:59 EEST / UTC +2). Early applications encouraged.
Required documents:
- Certified copies of Bachelor’s and Master’s degree certificates and transcripts (with Diploma Supplement, if applicable).
- Curriculum Vitae (preferably Europass format).
- List of publications (if available, with indication of individual contributions).
- Motivation letter (max. 1 page) outlining qualifications, research experience, and future career goals.
- References: Contact details of at least two referees (included in CV).
- Proof of residence over the last 3 years.
Please send your application documents as a single PDF to valeria.lopez-salazar@tum.de
Contact
- Professor, Supervisor, Achim Lilienthal (TUM): achim.j.lilienthal@tum.de
- Valeria Salazar, Recruitment Coordinator: valeria.lopez-salazar@tum.de
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Kontakt: achim.j.lilienthal@tum.de, valeria.lopez-salazar@tum.de