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Doctoral Thesis: Road-condition monitoring solutions for autonomous transportation systems
vor 3 Monaten
The industrial doctorate at Infineon: Pursue a doctoral degree at a university and gain professional experience simultaneously - an ideal start for your career. Advance your research with us and profit from our vast network of doctoral candidates and the expertise of a university. Mentorship is handled by both professors and dedicated Infineon employees. We are offering a PhD thesis dealing with "Road condition monitoring concepts and approaches based on multiple types of sensors." Road-condition monitoring solutions for autonomous transportation systems (ATS) based on radar and other types of sensors: To ensure a safe and robust operation of ATS the environment they are operating in has to be monitored to identify safety critical conditions as early as possible to trigger proper mitigation actions. One central element of the operating environment represents the road network, vehicles are driving along. Therefore, the road condition itself is referred to a safety critical environmental parameter, especially present road cracks, potholes, black-ice, etc. represent safety critical hazards. Modern autonomous vehicles get deployed for a specific operational design domain (ODD) described by the road network, environmental conditions and dynamic elements the vehicle is able to handler during the operation. This in turn forces the vehicle to monitor the current ODD during runtime to analize if its current operating conditions are within the approved ODD boundaries or not. This ODD monitoring task includes the road condition monitoring discipline as a central element. Infineon wants to explore possibiliteis in terms of concepts and approaches to identify the current road condition based on captured radar and other sensor data. Especially the variety of road condition attributes which can be identified together with a corresponding confidence are of interest in this research field. Radar and other sensors such as ultrasound are expected to enter every future automated vehicle to detect objects in terms of vulnerable road users (VRUs) and traffic participants in terms of cars, trucks, etc. Therefore, as they are already installed, the target should be to explore which road conditions can be detected with radar sensors in addition to objects and which road condition elements need other sensor types to be installed in future vehicles. The research will be performed in the Enablers & Emerging Trends group within the Research and Development Funding department at Infineon Technologies AG, Neubiberg. The Thesis will be written in cooperation with the University of Granada, under the supervision of Prof. DiegoP. Morales.
Quick Info LocationMunich (Germany) Entry level0-1 year Job IDHRC Start dateSep 01, 2024 TypeFull time ContractTemporary Workplace typeHybrid Job descriptionThe tasks within the thesis will consist of:
- Exploration of radar and other sensor data for autonomous transportation applications
- Investigation and development of algorithms for radar and other sensor data processing and the fusion of the data
- Development of efficient monitoring algorithms for edge devices
- Evaluation of the developed algorithms against the state-of-the-art
- Scientific research studies regarding road condition monitoring concepts with multiple different sensors and approaches
- Collaboration with University researchers and PhDs at Infineon performing their research in the area of AI and environmental sensor s and collaboration in European and German funded projects with industrial and academic partners.
- Set up of demonstration solutions and implementation of radar- and other sensor-based road condition monitoring algorithms as well as fusion approaches
A doctoral student is a research enthusiast,
› interests are scientific research combined with the passion for Infineon's innovative products and applications.
› enjoys working in an industrial environment in combination with an Infineon partner university.
› appreciates open communication and the contribution of an international environment.
› is thus an excellent candidate for a further academic or industrial career after completion of their thesis.
As the ideal candidate you:
- Are eligible for full-time PhD studies
- Have a university master degree in computer science, electrical engineering or equivalent with focus on embedded systems, data mining and machine learning for smart systems
- Have basic knowledge (physical principles, etc.) about radar and/or other sensors such as ultrasound
- Are experienced with AI algorithms for processing and fusion of sensor data
- Have basic knowledge about signal processing in the time and frequency domain
- Are experienced in demo system set up
- already gained some industry experience, fluent English and basic German skills
What we offer you at Campeon
In our headquarters in Neubiberg near Munich, more than 6000 employees are working in research & development, several central functions, IT and many more.
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Why UsDriving decarbonization and digitalization. Together.
Infineon designs, develops, manufactures, and markets a broad range of semiconductors and semiconductor-based solutions, focusing on key markets in the automotive, industrial, and consumer sectors. Its products range from standard components to special components for digital, analog, and mixed-signal applications to customer-specific solutions together with the appropriate software.
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This means we embrace diversity and inclusion and welcome everyone for who they are. At Infineon, we offer a working environment characterized by trust, openness, respect and tolerance and are committed to give all applicants and employees equal opportunities. We base our recruiting decisions on the applicant ́s experience and skills.
We look forward to receiving your resume, even if you do not entirely meet all the requirements of the job posting.
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Sophia Dechant
Recruiter
Wir bilden die gesamte Wertschöpfungskette für Halbleiter ab: von der Forschung & Entwicklung über die Produktion und Vertrieb & Marketing bis hin zur IT und Zentralfunktionen.
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