PhD position (m/f/d) in the field of Applied Signal Processing and Machine Learning

Responsibilities

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 ML-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.

Admission Requirements

• Completed M.Sc. degree in computer science, information and computer technology, physics, electrical engineering or similar

Desired Qualification

• Good programming skills (Python)
• Basic knowledge of machine learning and signal processing
• Excellent communication skills, fluency in English

We Offer

We offer an annual gross salary of at least € 52,007.20 for a fulltime position. An overpayment based on qualification and experience is possible.

Graz University of Technology aims to increase the proportion of women, in particular in management and academic staff, and therefore qualified female applicants are explicitly encouraged to apply. Preference will be given to women if applicants are equally qualified.

Graz University of Technology actively promotes diversity and equal opportunities. Applicants are not to be discriminated against in personnel selection procedures on the grounds of gender, ethnicity, religion or ideology, age, sexual orientation (Anti-discrimination).

People with disabilities and who have the relevant qualifications are expressly invited to apply.

About us

Graz University of Technology is the longest-established university of technology in Austria. Here, successful teams of students, talented up-and-coming scientists, ambitious researchers and a lively start-up scene enjoy an inspirational environment as well as access to top-quality equipment. And all this in one of the most innovative and livable regions in Europe. TU Graz offers an inspiring working environment with outstanding infrastructure and service-oriented university management.

Univ.-Prof. Dipl.-Ing. Dr.mont.Franz Pernkopf