Three vacant positions for fully employed University Asisstant’s at the Chair of Cyber-Physical-Systems on the Department of Product Engineering at the earliest possible date or beginning on 15th of June in a 4-year term of employment – RefID: 2103WPW
3 positions for fully employed University Assistant’s at the Chair of Cyber-Physical-Systems on the Department of Product Engineering at the earliest possible date or beginning on 15th of June in a 4-year term of employment. Salary Group B1 to Uni-KV, monthly minimum charge excl. SZ.: € 2.971,50 for 40 hours per week (14 times a year), actual classification takes place according to accountable activity-specific previous experience.
The following doctoral theses are available:
Fundamentals of learning methods for autonomous systems.
The goal is to make autonomous learning systems such as industrial robot arms, humanoid or mobile robots
suitable for everyday use. To achieve this, large amounts of data must be processed in a few milliseconds (Big
Data for Control) and efficient learning methods must be developed. In addition, safe human-machine interaction
must be ensured when dealing with the autonomous systems. For this purpose, novel stochastic motion learning
methods and model representations for compliant humanoid robots will be developed.
Fundamentals of stochastic neural networks.
Modern deep neural networks can process large amounts of data and calculate complex predictions. These
methods are also increasingly used in autonomous systems. A major challenge here is to integrate measurement
and model uncertainties in the calculations and predictions. For this purpose, novel neural networks will be
developed that are based on stochastic computations that enrich predictions with uncertainty estimations. The
neural networks will be used in learning tasks with robotic arms.
Robot learning with embedded systems.
Modern robot systems are equipped with complex sensors and actuators. However, they lack the necessary
control and learning methods to solve versatile tasks. The goal of this thesis is to develop novel AI-based sensor
systems and to integrate them into autonomous systems. The developed algorithms will be applied in mobile
computers and tested on realistic industrial applications with robotic arms.
What we offer:
The opportunity to work on research ideas of exciting modern topics in artificial intelligence and robotics, to develop your
own ideas, to be part of a young and newly formed team, to go on international research trips, and to receive targeted
career guidance for a successful scientific career.
Completed master's degree in computer science, physics, telematics, statistics, mathematics, electrical engineering,
mechanics, robotics or an equivalent education in the sense of the desired qualification. Willingness and ability for scientific
work in research including publications with the possibility to write a dissertation.
Desired additional qualifications:
Programming experience in one of the languages C, C++, C#, JAVA, Matlab, Python or similar. Experience with Linux or
ROS is advantageous. Good English skills and willingness to travel for research and to give technical presentations.
Reference number: 2103WPW
End of Application: 2021-06-30
The Montanuniversitaet 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.
For the application please use the online form on the homepage:
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