Host: TUHH (DE) Main supervisor: Prof. Christian Schuster (TUHH, DE) Co-supervisors/mentors: Dr.ir Stanislav Kovar (TBU, CZ) / Prof. Matthias Mnich (TUHH, DE) / Nexperia (DE) Duration: 36 months Required profile: Electrical Engineering, Physics, or Data Science Desirable skills/interests: Electromagnetics, Electromagnetic Compatibilty, Machine Learning, Artificial Intelligence Objectives: This DC project aims to extend the state of the art in application of methods of machine learning (ML) to the field of electronic computer aided design (ECAD). Specifically, it aims to develop, train, optimize and evaluate ML methods for simulation and optimization of high-speed packages for discrete devices in combination with generating and using an adaptive database. The main objective is to adapt ML methods which model and ultimately replace the existing design process in most steps and hierarchies. Secondments (2-4 months in total): Nexperia (DE) and IETR (CNRS, FR).