Technical Internship - Ultra-Precision Metrology and Data Analysis

Job Description:

Imagine what you could do here? At Apple, new ideas have a way of becoming phenomenal products, services, and customer experiences very quickly. Bring passion and dedication, and there's no telling what you could accomplish. Every role at Apple is crafted around our intention to leave the world a better place than we found it! Apple's Hardware Engineering R&D Division in Japan is seeking talented and enthusiastic students to participate in a Technical Internship focused on Ultra-Precision Metrology and Precision 3D Point Cloud Data Analysis. The team pursues advancement of performance in our optical components through improving lens manufacturing processes and developing new optical elements.
Specific projects and assignments will be tailored by our engineers based on each student's individual strengths and background. Some general responsibilities may include: -Operate ultra-precision measuring instruments to measure lenses and molds -Evaluate surface accuracy using 3D point cloud data -Improve existing systems through data analysis and process development -Propose and implement innovative ideas to enhance the current metrology system ** The start timing and duration are flexible and will be adjusted to each selected intern's study schedule to avoid interfering with ongoing university studies and research.
Interest in ultra-precision metrology and 3D point cloud data analysis Outstanding academic achievements in your field of study Proficiency in programming languages such as MATLAB, Python, C/C++/C#, Swift, and Go is preferred. Ability to plan and execute experiments independently and creatively Fluent in English and Japanese, demonstrating not only strong verbal communication skills but also excellent writing and presentation skills. Authorization for work in Japan.
Project experience in ultra-precision metrology Experience performing statistical analysis on large 3D datasets using custom programs Understanding of coordinate transformation for 3D data and nonlinear least squares methods