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Ethan joined Markel in 2024 as an assistant tax consultant after graduating from the University of Sheffield with a Master's degree in Mechatronic and Robotic Engineering (MEng). His Master's dissertation focused on developing AI for application in the medical sector, utilising deep learning techniques to create a system for automatic segmentation and texture analysis of patients' MRI muscle scans.
Ethan is proficient in programming languages Python, C++, and MATLAB. He has experience with Autodesk 'Fusion 360' (3-D Computer Aided Design) Software, Electrical Engineering, Machine Vision, Deep Learning, and Control Systems Design and Analysis. Ethan assists a wide range of clients with R&D tax claims, particularly in the engineering and software industries.