Doctoral Thesis: Trustworthy Generative AI for Consumer Sensors and Power Applications (f/m/div)

<![CDATA[ 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 offer a doctoral thesis that deals with the development of trustworthy AI algorithms for Large Language Models (LLM), embodied multi-modal LLM, and Generative AI-based applications. The student will be responsible for integrating the technical dimensions of trustworthiness into the early stages of design and for ensuring that the solutions developed comply with regulations such as the EU AI Act.

The thesis will be written in cooperation with University of Magdeburg and under the supervision of Professor Fabian Lurz.

Job Description
The tasks within the thesis will consist of:

• Research on trustworthy AI algorithms for LLM, embodied multi-modal LLM, and Generative AI based applications with focus on accuracy, robustness, fairness, transparency, explainability, cybersecurity, and human oversight
• Application of selected methods to available sensor data and performance validation in real world scenarios
• Formulation of hardware requirements for Generative AI algorithms and related trustworthy enhancements
• Derivation of technical benchmarks for EU AI harmonized standards and regulations
• Focus on microphone-based applications, sensor fusion platforms and perception for service robots

The learnings out of the thesis will lead to

• enhance the understanding of LLMs and Generative AI in real-world applications relevant to Infineon
• foster innovation around smart sensor products and power electronics.

Your Profile
A doctoral student is a research enthusiast,
› …whose interests are scientific research combined with the passion for Infineon’s innovative products and applications.
› …who enjoys working in an industrial environment in combination with an Infineon partner university.
› …who appreciates open communication and the contribution of an international environment.
› …and 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 and have a master’s degree in Computer Science, Electrical Engineering, Mathematics or a related field with very good grades.
• Have practical experience in machine learning, with a focus on deep learning methods and generative AI.
• Provide a solid background in probability theory and statistics.
• Are experienced with deep learning frameworks like Tensor flow or PyTorch.
• Have a solid understanding of signal processing techniques.
• Have strong problem-solving abilities and the capability to analyze complex sensor datasets.
• Are able to work in a fast-paced environment and meet deadlines.
• Possess very good language skills in English and ideally German.

Contact:
Sophia Dechant

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The PSS division powers decarbonization and digitalization with a wide range of energy-efficient and digital solutions. PSS semiconductors help avoid carbon emissions, use resources sustainably, manage power effectively and intelligently, give ‘things’ smart senses, and process data quickly and reliably. The portfolio includes power, connectivity, RF, and sensor system technologies to develop smaller, lighter, smarter, and more efficient solutions for consumer devices, smart home/building applications, robotics, computing and data centers, charging devices, power tools, and much more.
The next generation of silicon and wide-bandgap (SiC and GaN) solutions provides unparalleled performance and reliability for 5G, big data, and renewable energy applications. These materials are paving the way for further energy and carbon savings. Highly precise XENSIV™ sensor solutions are enabling IoT devices to react intuitively to their surroundings for seamless user interactions while audio amplifiers bring exceptional sound experiences to smart speakers and other audio use cases.

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