Author: Elmar Rueckert

image_pdfimage_print

1 PhD Position – EU Doctoral Network – Refracteur

Elmar Rueckert job
 

The Chair of Cyber-Physical Systems at Montanuniversitaet Leoben in Austria is offering a full-time position (100% employment) starting as soon as possible in collaboration with Siemens within the EU-funded MSCA Doctoral Network project REFFRACTEUR.

  • Living Allowance of €4010/month (This is a gross value (employer and employee taxes will be removed) and will be subject to a country-specific correction factor)
  • Mobility allowance: €710/month.
  • Family allowance*: €660/month (depending on family situation).

• Duration:

• PhD: 3 years (structured as 18 months at Siemens and 18 months at Montanuniversitaet Leoben)

more details on the recruitment procedure and benefits can be found here: https://www.reffracteur.eu/reffracteur-phd-recruitment-procedures/

About the Position

The REFFRACTEUR (Digital REFractory FRAmework for a Carbon-neutral and Resilient indusTry in EURope) project brings together a unique consortium across academia and industry to advance sustainable refractory materials. It trains doctoral candidates through interdisciplinary research combining materials science, digital technologies (AI and digital twins), and sustainability, with strong industrial integration.

This specific position corresponds to:

PhD 03 – Semantic data integration and cloud-based industrial platforms for circular refractory life cycle applications

The research focuses on developing digital and AI-driven solutions for circular economy applications in industrial environments, including:

• Semantic data integration across heterogeneous industrial data sources

• Development of cloud-based industrial platforms for lifecycle data management

• Integration of sustainability indicators into digital decision-support systems

• Data-driven support for material selection, design, and end-of-life strategies

• AI-based methods for analyzing industrial processes and lifecycle data

This position combines cutting-edge research in AI, data engineering, and industrial digitalization with real-world applications in collaboration with Siemens, including a strong focus on circular economy and sustainability in industry.

What we offer

• A dynamic and collaborative research environment in artificial intelligence and industrial digitalization

• Joint supervision between academia and industry (Montanuniversitaet Leoben & Siemens)

• A structured international doctoral training program within an EU MSCA network

• The opportunity to work on real-world industrial challenges with high impact

• Access to state-of-the-art research infrastructure and industrial platforms

• International research collaborations and conference travel opportunities

• Targeted career guidance for academic and non-academic career paths

Requirements

• Master’s degree in Computer Science, Physics, Mechanics, Robotics, or a related field

• Strong motivation for scientific research and publications

• Ability to work independently and collaboratively in an interdisciplinary team

• Interest in pursuing a PhD in an international and industrial context

Desired additional qualifications

• Strong programming skills

• Background or interest in Artificial Intelligence and data-driven methods

• Familiarity with cloud platforms, data engineering, or industrial IT systems

• Experience with AI libraries and frameworks (e.g., TensorFlow, PyTorch)

• Strong English communication skills (written and spoken)

• Willingness to travel and spend extended research periods at Siemens and other project partners

Application & Materials

A complete application includes:

  1. Curriculum Vitae (CV) (detailed)

  2. Letter of Motivation – clearly stating your interest in this specific PhD position

  3. Master’s Thesis (PDF or link)

  4. Academic Certificates (Bachelor’s and Master’s degrees)

Optional but beneficial:

  1. Letter(s) of Recommendation

  2. Contact Information for References (name, email, phone)

  3. Previous Publications (PDFs or links)

Application deadline: Open until the position is filled.

Online Application via Email: Please send your application files to rueckert@unileoben.ac.at

The Montanuniversität Leoben intends to increase the number of women on its faculty and therefore specifically invites applications by women. Among equally qualified applicants women will receive preferential consideration.

 

1 PhD Position – Humanoid Robot Learning (FFG RoboWork)

Elmar Rueckert job
The Chair of Cyber-Physical Systems at Montanuniversitaet Leoben in Austria  is offering a full-time position (100% employment) starting as soon as possible.

• Employment Type: Full-time (40 hours/week) – PhD student or Postdoc

• Salary: €3,776.10/month (Ph.D.) or €5,014.30/month (postdoc), paid 14 times per year 

• Duration: 
• PhD: up to 4 years (including completion of the doctoral degree)
• Postdoc: initially 2 years, with the option for extension


About the Position

The RoboWork project aims to unlock the full potential of humanoid robots in industrial environments, paving the way for their effective and reliable deployment in future workplaces. 
 
We are at the forefront of developing cutting-edge machine learning algorithms for robot skill learning for industrial applications, including:

• Whole-body control of humanoid robots in teleoperation and learning-based environments
• Robot skill learning using modern generative and reinforcement learning approaches
• Multi-modal robot control utilizing vision, acoustic, and tactile sensing
• Simulation-based learning and sim-to-real transfer for robust deployment
• Adaptive manipulation and motion planning in dynamic and unstructured environments

This research position will focus on multiple aspects of these topics, with a special emphasis on humanoid robot skill learning of industrial applications. 


What we offer

• A dynamic and collaborative research environment in artificial intelligence and robotics

• The opportunity to develop your own research ideas and work on cutting-edge projects

• Access to state-of-the-art lab facilities

• International research collaborations and conference travel opportunities

• Targeted career guidance for a successful academic and research career



The figure below illustrates an example application of the project, focusing on learning manipulation tasks with objects on a conveyor belt.

Requirements


• For Ph.D. candidates: Master’s degree in Computer Science, Physics, Telematics, Statistics, Mathematics, Electrical Engineering, Mechanics, Robotics, or a related field
 
• For postdoctoral candidates: A completed Ph.D. in a topic related field 

• Strong motivation for scientific research and publications

• Ability to work independently and collaboratively in an interdisciplinary team

• Interest in writing a PhD dissertation



Desired additional qualifications


• Programming experience in C, C++, C#, Java, MATLAB, Python, or a similar language

• Familiarity with AI libraries and frameworks (e.g., TensorFlow, PyTorch)

• Strong English communication skills (written and spoken)

• Willingness to travel for research collaborations and technical presentations



Application & Materials


A complete application includes:

1. Curriculum Vitae (CV) (detailed)

2. Letter of Motivation – State if you apply for the Ph.D. or the postdoc position

3. Master’s or Ph.D. Thesis (PDF or link)

4. Academic Certificates (Bachelor’s and Master’s degrees)

Optional but beneficial:

5. Letter(s) of Recommendation

6. Contact Information for References (name, email, phone)

7. Previous Publications (PDFs or links)



Application deadline: Open until the position is filled.

Online Application via Email: Please send your application files to rueckert@unileoben.ac.at


The Montanuniversität Leoben intends to increase the number of women on its faculty and therefore specifically invites applications by women. Among equally qualified applicants women will receive preferential consideration.

Digital Underground Mining: Sensorik, KI und IoT für Echtzeitüberwachung und Prozessoptimierung im Untertagebau (MineView)

Elmar Rueckert projects_thirdparty

Rohstoffe 2024

FFG Projekt 15/11/2025-14/11/2028

Ziel des Projekts MineView ist die Entwicklung eines digitalen Überwachungssystems, das letztendlich eine ganzheitliche und kontinuierliche gebirgsmechanische Zustandsbewertung von untertägigen Bauwerken ermöglicht. Durch den Einsatz von Robotern, Sensorik und KI werden bestehende Überwachungsmethoden revolutioniert und eine neue Ära der digitalen Bergwerksüberwachung eingeleitet.

Der Lehrstuhl wird im Zuge dieses Projektes den Einsatz von autonomen Robotern und/ oder Drohnen für die Zustandserfassung und Integration in bestehende Produktionsabläufe erforschen. 

Bild, akustische und andere Daten werden systematisch erfasst und mit maschinellen Lernmethoden ausgewertet. Ziel ist die automatische Erkennung von Mustern in gebirgsmechanischen Daten sowie in Umweltdaten. Die Vorhersagen der entwickelten  Lernmethoden sollen in Frühwarnsystemen kritische Zustände frühzeitig identifizieren und so zur Sicherheit im Untertagebau beitragen.

Projektconsortium

  • Montanuniversität Leoben
    • Lehrstuhl für Bergbaukunde, Bergtechnik und Bergwirtschaft (BBK) 
    • Lehrstuhl für Cyber-Physical-Systems (CPS)
  • RHI Magnesita

Fördergeber

  • Österreichische Forschungsförderungsgesellschaft mbH (FFG)

Humanoide Roboter und multimodale Manipulationstechnologien für die industrielle Produktion und Logistik (RoboWork)

Elmar Rueckert projects_thirdparty

Schlüsseltechnologien im produktionsnahen Umfeld 2025

FFG Projekt 08/2026-07/2029

Abbildung: Schematische Darstellung existierender Technologien (a bis g), die im industriellen Umfeld engesetzt werden (h). 

Projektconsortium

  • Montanuniversität Leoben
    • Forschungs- und Innovationsservice Montanuniversität (Administrativer Koordinator)
    • Lehrstuhl für Automation und Messtechnik
    • Lehrstuhl für Cyber-Physical-Systems
  • Knapp AG
  • Boehlerit GmbH&Co.KG
  • RISKSEN

Fördergeber

  • Österreichische Forschungsförderungsgesellschaft mbH (FFG)

Cynthia Ani

Elmar Rueckert people_student_assistants

Student Assistant at the Montanuniversität Leoben

Cynthia_Ani

Short bio: Cynthia Ani joined CPS in March 2026.

She is studying data science in her final year of her masters program at the TU Graz and industrial data science in Leoben. Her research interests includes AI and in particular modern machine learning methods. 

Research Interests

  • Data Science
  • Machine Learning
  • Foundation Models (AI)

Contact

Cynthia Ani
Student Assistant at the Chair of Cyber-Physical-Systems
Montanuniversität Leoben
Franz-Josef-Straße 18,
8700 Leoben, Austria 

Email:cynthia-ugonna.ani@stud.unileoben.ac.at

Peyman Kahrizi

Elmar Rueckert people_student_assistants

Student Assistant at the Montanuniversität Leoben

Festes Seitenverhältnis

Short bio: Peyman Kahrizi joined CPS in 2026.

He is currently working on his Master’s thesis at Montanuniversität Leoben. His research focuses on real-time dense SLAM using RGB-D sensors, including dense 3D reconstruction with Gaussian Splatting, pose estimation using GICP, and semantic scene representation based on CLIP language embeddings.  His work is implemented primarily in Python using Open3D. 

Research Interests

  • 3D Reconstruction
  • SLAM
  • Pose Estimation
  • Machine Learning

Contact

Peyman Kahrizi
Student Assistant at the Chair of Cyber-Physical-Systems
Montanuniversität Leoben
Franz-Josef-Straße 18,
8700 Leoben, Austria 

Email: peyman.kahrizi@stud.unileoben.ac.at

Katharina Binder (Secretary)

Elmar Rueckert people_secretariat

Secretary

Short bio: Katharina Binder joined the CPS team in November 2025 and is responsible for organizational and administrative matters. She holds a diploma from the International Bilingual Business College in Hetzendorf with a focus on marketing. Before that, she completed her secondary education at the Higher Institute for Tourism in Krems, specializing in tourism management. She also studied political science at the University of Vienna.

Research Interests

  • Cyber-Physical-Systems 
  • Modern Technologies 
  • Learning Machines and Robotics

Contact

Katharina Binder
Sekretariat des Lehrstuhls für Cyber-Physical-Systems
Montanuniversität Leoben
Franz-Josef-Straße 18, 
8700 Leoben, Austria 

Phone:  +43 3842 402 – 1901
Email:   sandra.binder@unileoben.ac.at 
Web:  https://cps.unileoben.ac.at

Guenther Hutter, M.Sc.

Elmar Rueckert people_accademic

Ph.D. Student at the Montanuniversität Leoben

Short bio: Mr. Guenther Hutter will start at CPS on 1st of September in 2025. 

Günther Hutter is an experienced educator and researcher in the fields of computer science, automation, and cybersecurity. He holds degrees in Software Design and Advanced Security Engineering from the University of Applied Sciences Kapfenberg, both awarded with distinction. His professional background includes leadership roles in software development and PLM integration, with a focus on software architecture, data quality, and industrial IT systems.

 

Since 2017, he has served as head of the IT & Smart Production division at HTL Leoben, where he is responsible for curriculum development and interdisciplinary laboratory instruction across multiple engineering domains. His teaching and research interests encompass embedded systems, industrial communication, IT security, and open-source educational technologies. As founder of bytebang e.U., he also engages in applied research and consulting in IoT, data visualization, and system integration.

Research Interests

  • Machine Learning
  • Robotics
  • Computer Vision

Contact & Quick Links

Guenther Hutter, M.Sc.
Doctoral Student supervised by Univ.-Prof. Dr. Elmar Rueckert.
Montanuniversität Leoben
Roseggerstrasse 11 , 
8700 Leoben, Austria 

Phone:  +43 3842 402 1901
Email:   TBA 
Web Work: CPS-Page
Chat: WEBEX

Personal Website: bytebang.at
GitHub: bytebang
LinkedIn: Günther Hutter

Publications

Meeting Notes

[/aam]