The Department of Mathematics and Computer Science at Eindhoven University of Technology (TU/e) is seeking a highly motivated PhD student to join a cutting-edge research project on scalable and safe artificial intelligence (AI) for semiconductor metrology. This project is conducted in close collaboration with ASML AI Research and is part of the NWO TTW Perspectief funded research program 'Foundation for Industry (FIND) - Large AI models for a resilient high-tech industry.' The research focuses on developing advanced methods for model distillation, robustness, and efficient, reliable inference in real-world semiconductor manufacturing environments.

The PhD candidate will work on pushing the boundaries of multimodal foundation models, combining data from multiple metrology sources to achieve high accuracy in early-stage manufacturing and across diverse use cases. As manufacturing processes mature, the research will address efficient fine-tuning and distillation of models under strict data and privacy constraints, ensuring performance guarantees for critical failure modes. The project aims to enable machine learning models to adapt to evolving requirements in accuracy, speed, and defect detection throughout the lifecycle of semiconductor process nodes, with minimal adaptation across different customers and use cases.

The successful candidate will be formally employed within the Data and AI cluster at TU/e and supervised by prof.dr. Mykola Pechenizkiy and dr. Ghada Sokar, with close collaboration with dr. Jan Jitse Venselaar and dr. Jacek Kustra from ASML AI Research. The position offers access to national and institutional computing infrastructure, including the TU/e HPC cluster SPIKE-1 and ASML HPC cluster, as well as relevant datasets. The candidate is expected to spend time at both TU/e and ASML locations, benefiting from a vibrant academic and industrial research environment.

Applicants should have a master's degree in AI, Machine Learning, Data Science, Computer Science, or a related field, with a strong background in machine learning and programming. Experience in model distillation, adaptation, and industrial collaboration is advantageous. Excellent academic writing, communication skills, and fluency in English (C1 level) are required.

The position is fully funded for four years, with a competitive salary (€3,059–€3,881/month), year-end bonus, vacation pay, pension, parental leave, and additional benefits such as training programs, technical infrastructure, childcare, sports facilities, and allowances for commuting and internet costs. International candidates may benefit from the 30% tax compensation scheme. The application deadline is March 18, 2026. For more information and to apply, visit the official vacancy page.