Mykola Pechenizkiy

Eindhoven University of Technology, a leading research institution in the Netherlands, is offering six PhD positions focused on advancing design automation and diagnostics in the semiconductor industry. The university is renowned for its collaborative culture and strong ties to high-tech industries, particularly in the Brainport region. These positions span the departments of Mechanical Engineering, Electrical Engineering, and Mathematics and Computer Science, and are aimed at solving complex, multidisciplinary challenges in system-level modelling, analysis, design, and synthesis for semiconductor equipment, especially lithography machines. The research topics include automated computational design synthesis of system topologies, scenario-based system-level performance engineering, timing-aware distributed supervisory controller synthesis, AI-driven legacy system explanation and refactoring, data mining for diagnostics using knowledge graphs and foundation models, and automating health monitoring in semiconductor equipment. Each project is supervised by leading academics and involves collaboration with industry partners such as ASML AI Research. Candidates will work in a vibrant, interdisciplinary environment, receive comprehensive training, and benefit from excellent employment conditions including a four-year contract, competitive salary, bonuses, pension, paid leave, and support for international staff. Applicants must have a master’s degree in a relevant field and demonstrate strong analytical, problem-solving, and teamwork skills. Specific expertise in software engineering, programming, cyber-physical systems, formal methods, AI, data mining, control theory, and related areas is required for certain positions. Applications are accepted online until November 30, 2025, and should include a cover letter, CV, and references. The university provides a supportive infrastructure, professional development opportunities, and a dynamic campus environment. For more information, candidates are encouraged to contact the listed supervisors or HR services.

Eindhoven University of Technology is offering six PhD positions focused on advancing design automation, diagnostics, and AI applications for complex semiconductor systems, particularly lithography machines. These positions span the departments of Mechanical Engineering, Electrical Engineering, and Mathematics and Computer Science, and are designed to address the limitations of current domain-specific automation solutions by developing holistic, system-level approaches. The research topics include automated computational design synthesis of system topologies, scenario-based compositional system-level performance engineering, timing-aware distributed supervisory controller synthesis, AI-driven legacy system explanation and refactoring, data mining for diagnostics using knowledge graphs and foundation models, and automating health monitoring in semiconductor equipment. Each project is supervised by leading academics and, in some cases, involves collaboration with industrial partners such as ASML AI Research. Candidates will work on cutting-edge challenges such as system architecture exploration, model-based performance engineering, supervisory control synthesis, generative AI for software maintenance, advanced diagnostic frameworks, and predictive monitoring technologies. Applicants should have strong backgrounds in relevant fields, with specific skills required for each position, such as software engineering, formal methods, control theory, and AI. The positions offer the opportunity to contribute to innovation in the Brainport region and beyond, working in interdisciplinary teams and with internationally recognized industrial partners. Funding details are not specified in the announcement. Interested candidates should apply online via the AcademicTransfer link, submitting their CV, motivation letter, and transcripts, and indicating their preferred PhD project(s).

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.

Join the Data and AI cluster at the Department of Mathematics and Computer Science, Eindhoven University of Technology, as a PhD candidate in scalable and safe AI for semiconductor metrology. This project aims to push multimodal generative AI beyond the lab, focusing on advanced model distillation and robustness methods to enable efficient and reliable inference for real-world challenges in the semiconductor industry. The research is motivated by the need for high-accuracy metrology in next-generation manufacturing processes, leveraging multimodal foundation models that combine data from multiple sources. As manufacturing matures, these models are specialized through efficient fine-tuning and distillation, improving throughput and maintaining performance guarantees on critical failure modes. The PhD project centers on developing data-efficient methods for fine-tuning and distillation under strict data and privacy constraints, providing performance guarantees for specific downstream tasks. Customer data is often highly constrained, with limited and imbalanced datasets and strict privacy requirements. The project addresses evolving model performance requirements across the lifecycle of a process node, adapting to changing accuracy, speed, and defect-detection needs. The goal is to develop state-of-the-art techniques that facilitate robust metrology models and faster time-to-recipe across semiconductor process maturity stages. Supervision is provided by Professor Mykola Pechenizkiy and Dr. Ghada Sokar at TU/e, in close collaboration with Dr. Jan Jitse Venselaar and Dr. Jacek Kustra from the ASML AI Research Team. The candidate will spend time at both TU/e and ASML locations, benefiting from access to national computing infrastructure, TU/e HPC cluster SPIKE-1, ASML HPC cluster, ASML datasets, and potential custom data through collaboration with IMEC. The project is part of the NWO TTW Perspectief funded research program 'Foundation for Industry (FIND)'—Large AI models for a resilient high-tech industry. Applicants must have a master's degree in AI, Machine Learning, Data Science, Computer Science, or a closely related field, with a solid background in machine learning and strong programming skills. Enthusiasm for application-inspired ML research and interest in industrial collaboration are essential. Experience in model distillation, adaptation, and related topics is advantageous. Good academic writing and communication skills and fluency in English (C1 level) are required. The position offers full-time employment for four years, with an intermediate assessment after nine months. Teaching tasks comprise a minimum of 10% of employment, with a maximum of 15% per year. Salary is in accordance with the Collective Labour Agreement for Dutch Universities, scale P (€3,059–€3,881/month), plus a year-end bonus (8.3%), annual vacation pay (8%), pension scheme, paid pregnancy and maternity leave, partially paid parental leave, commuting and home working allowances, and a 30% tax facility for international candidates. Additional benefits include high-quality training programs, excellent technical infrastructure, on-campus childcare, sports facilities, and support from the Staff Immigration Team. To apply, submit your application online via the provided link. Include a cover letter, CV, MSc thesis or academic writing sample, and contact information for two references. Priority is given to complete applications. The vacancy remains open until filled, with a deadline of March 18, 2026. Applications sent by email or post will not be processed. For further information, contact Professor Mykola Pechenizkiy ([email protected]) or HR services M&CS ([email protected]).