AI-Driven Process Optimization for TEM Automation

Imec; Vlaams-Brabant; On-site; EUR 10,000 - 15,000; Full time

Job summary

imec is seeking a highly motivated Master student for an internship focused on AI-driven optimization in TEM automation. You will develop and evaluate AI/ML models that enhance process robustness and performance, integrating them into ETM recipes and automation workflows.

Collaboration across a multidisciplinary team is expected, with ownership of your projects. The internship lasts 3 months, targets students in Computer Science or Physics, and is based at imec's facilities in Belgium.

Qualifications

• Master student eager to apply AI/ML to process optimization.
• Background in CS or physics with strong analytical skills.
• Experience with data-driven modeling is a plus.

Responsibilities

• Develop and evaluate AI/ML models for ETM process recipes.
• Analyze complex process data to identify key parameters.
• Collaborate in a multidisciplinary team and own projects.

Skills

AI/ML modeling

Data analysis

Python

Collaborative work

Education

Master in Computer Science

Master in Physics

Job description

AI-Driven Process Optimization for TEM Automation

We are looking for a highly motivated intern with a strong interest in artificial intelligence, machine learning, and data-driven process optimization. A master student pursuing any of the above mentioned relevant track. During the internship at imec, the candidate will develop and evaluate AI/ML models that can be integrated into our ETM process recipes and automation workflows to improve process robustness, stability, and performance. The work will involve analyzing complex process data, identifying key parameters, and building predictive or adaptive models that support smarter recipe control. We are seeking a proactive and independent individual who is eager to learn, enjoys solving technical challenges, and is capable of collaborating within a multidisciplinary team while taking ownership of their projects.

Type of internship: Master internship Duration: 3 months Required educational background: Computer Science, Physics Supervising scientist(s): For further information or for application, please contact Jesus Felix Servin ([e-mail]) Reference code for this position is 2026-INT-343. Mention this reference code in your application. Only for self-supporting students.

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