With a strong foundation in theoretical and mathematical physics (MSc), Petr Lenhard has applied his analytical expertise across various fields throughout his career. As the CEO of Inference Technologies since 2015, he has led the development of cutting-edge predictive systems and AI-driven solutions for the semiconductor industry, helping manufacturers optimize yield, reliability, and efficiency through data-driven innovation.
Before founding Inference Technologies, he gained significant experience as an Automated Trading Strategies Developer at Trading and Research (2008–2015), where he specialized in building advanced trading models. His early career as a Research Assistant at the Czech Technical University in Prague was focused on "Deformations and Contractions of Lie Groups and Algebras" and teaching theoretical physics, which helped him develop both his technical expertise and ability to convey complex concepts. He is passionate about leveraging data and advanced analytics to drive innovation and transformation, particularly in highly complex and competitive industries like semiconductor manufacturing.
Relevant Publications:
In R&D we are developing cutting-edge predictive systems and flexible data analysis solutions tailored specifically for the semiconductor manufacturing industry. Leveraging years of expertise, our DeepFab technology suite is designed to harness the power of historical and real-time data to significantly enhance manufacturing outcomes, focusing on yield improvement, cost reduction, and product reliability.
The DeepFab technology includes:
• An advanced analytics platform that provides in-depth process and yield insights to optimize manufacturing efficiency.
• A powerful predictive system for smart product routing, ensuring the most efficient path for production based on real-time yield prediction.
• A latent defect screening tool that helps mitigate reliability risks by identifying potential latent defects before they impact the performance and reliability of the semiconductor device.
We are seeking a motivated intern for a summer position in Machine Learning Modeling, focused on developing models using semiconductor manufacturing data. The intern will work with our in-house GPU infrastructure in a Linux environment, leveraging Python and the PyTorch framework for deep learning. Responsibilities include data preprocessing, model development, and performance optimization. Ideal candidates should have strong Python skills, experience with PyTorch, and a passion for machine learning innovations. We value candidates who bring fresh ideas and are eager to explore the latest advancements in the field.
From June 9 to August 31, 2025 (adjustable at the discretion of the organisation)