PhD position in the field of Applied Signal Processing and Machine Learning
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- Wed, May 21, 2025
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The focus of this position is on the development of hybrid AI models for automotive radar data. This means that you will conduct state-of-the art research at the interface between classical physics-based signal processing and data-driven machine learning and publish at high ranking conferences and journals.
The project itself aims to develop an AI-aided radar system that is able to fuse radar information on a symbolic level. During the project we will focus on the following topics concerning:
- Enhancing performance at sensor-level: Develop multi-static radar signal models that incorporate angular, range (delay), and velocity (Doppler) parameters for coherent data fusion in distributed automotive radar sensors. Design machine learning enhanced radar preprocessing methods incorporating calibrated uncertainties.
- Reliability by higher-level integration: Merge classical Bayesian graphical models with AI components to enable scalable algorithms that account for uncertainties in a fully probabilistic manner and are able to fuse data at a higher level to improve system reliability in complex scenarios.
- Situation-aware sensor configuration: Develop active adaptation algorithms for next generation automotive radar systems guided by higher-level information. This will allow the system to concentrate on regions of high measurement uncertainty or critical relevance.
The hybrid nature of these AI-enhanced, model-based algorithms naturally accommodates uncertainty and provides a high degree of flexibility, crucial for safety-critical applications like automotive radar. In collaboration with Infineon, the opportunity is given to evaluate the developed hybrid methods on real automotive radar sensor architectures.
Required skills:
- M.Sc. degree in a relevant field (Computer Science, Information and Computer Engineering, Physics, Electrical Engineering, or similar)
- Good programming skills (Python)
- Basic knowledge of machine learning and signal processing
- Excellent communication skills, fluency in English
We offer:
- Interesting area of responsibility
- Flexible working schedule
- University’s sports program
- Safe and stable working environment
- Subsidy for public transport
- Exciting opportunities for professional and personal development
- Top research infrastructure and access to the latest technologies
- Public transport subsidy
- Workplace Health Management
- Shopping Discounts
- Possibility for Home-Office
- International training and teaching opportunities”
We offer a minimum annual gross salary based on full-time of EUR 52.007,20, overpayment possible depending on qualification and experience.
Graz University of Technology actively promotes diversity and equal opportunities. People with disabilities and who have the relevant qualifications are expressly invited to apply.
How to apply: Please send your application (CV, motivation letter, list of grades) to pernkopf@tugraz.at. The position is filled as soon as a suitable candidate is found.