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A leading research facility in additive manufacturing in Villach is seeking a PhD candidate for the position focused on advanced multi-axis 3D printing algorithm development. The ideal candidate holds a Master’s degree in a relevant field and possesses strong programming skills, particularly in Python. Responsibilities include algorithm development, integration into software platforms, and collaboration with interdisciplinary teams. The position offers a unique opportunity to contribute to innovative approaches in 3D printing technology.
ADMiRE is the Research Center for Additive Manufacturing, Intelligent Robotics, and Embedded Sensors at Carinthia University of Applied Sciences. We focus on developing practical, sustainable, and application-driven solutions in 3D printing and robotics. Our work emphasizes real-world impact, promotes environmental responsibility, and thrives on close collaboration with industry partners and society.
Open PhD-student position "Advanced Multi-Axis 3D Printing Algorithm Development and Integration"
The PhD candidate will work in Villach (CUAS) with the ADMiRE Research Center and is supervised by Univ.-Prof. Dr.- Ing. habil. Andreas Müller, Professor at Johannes Kepler University, Institute of Robotics.
Your profile:
We are looking for a motivated PhD candidate to contribute to the FFG-funded research project ESMA, particularly in the field of advanced multi-axis 3D printing. This work aims to develop novel slicing and toolpath algorithms, software integration, and real-time printing strategies for kinematically redundant robotic 3D printing systems.
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Open PhD-student position "Methodological Framework for Sensor Integration in Additive Manufacturing"
The PhD candidate will work in Villach (CUAS) with the ADMiRE Research Center and is supervised by Univ.-Prof. Dipl.-Ing. Dr. Hubert Zangl, Professor at Universität Klagenfurt.
Your profile:
We are looking for a motivated PhD candidate to contribute to the FFG-funded research project ESMA, particularly in the field of function integration in 3D printed structures. This work aims to develop a series of methods to make 3D printed structures smarter. The challenge lies in equipping various families of 3D-printed parts with sensing capabilities tailored to specific use cases.
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