Machine Learning for advanced Device Characterization and Chip Design

We are seeking a highly motivated and talented intern to join our team at imec, a leading research and innovation hub in nanoelectronics and digital technologies. As a Machine Learning Intern, you will assist in the development of a machine learning-based application for device characterization and design. You will work closely with our team of experts in device modeling, simulation, device designer, and machine learning to explore the potential of machine learning in advancing the state-of-the-art in device design and characterization.

 
Responsibilities:
 

• Assist in the development of machine learning models for device characterization and device design
• Investigate or implement various machine learning algorithms and techniques (e.g. supervised/unsupervised learning, deep learning) to analyze and predict device behavior
• Collaborate with the team to integrate machine learning models with existing device simulation and modeling tools
• Analyze and interpret results, identifying opportunities for improvement and optimization
• Contribute to the development of software tools and scripts to support machine learning-based device characterization and design
• Stay up-to-date with the latest advancements in machine learning and device modeling, and apply this knowledge to improve our research and development

Type of Project: Thesis; Combination of internship and thesis

Master's degree: Master of Science 

Master program: Computer Science 

Duration: 6 months 

Supervisor: Roel Wuyts (Computer Science) 

For more information or application, please contact Jerome Mitard (jerome.mitard@imec.be)

Imec allowance will be provided for students studying at a non-Belgian university.