ASPIRE Intern – Brain Science: Applying Machine Learning for Dynamic Autofocus in Transmission Electron Microscopy

The Allen Institute is dedicated to understanding the principles that govern life and advancing health. They are seeking an intern to develop automation tools for high-throughput transmission electron microscopy imaging while leveraging machine learning techniques for image quality improvement. Responsibilities Contribute to the efforts of the Connectomics department at the Allen Institute in developing automation tools for high-throughput TEM imaging of whole hemisphere samples Explore alternative parameter tuning approach by expanding on existing deep learning focus correction models Develop deep learning image correction methods using images acquired on TEMs Evaluate the utility of machine learning modeling project by integrating it into the modular software framework and comparing its output with classical computer vision approach Gain experience evaluating microscopy data for image quality, training machine learning models with TEM image data, and applying cutting-edge methods in computer vision to an image acquisition pipeline Skills Bachelor's degree Demonstrated commitment to science Must have completed a Bachelor's degree prior to the start of the program, and no earlier than December 1, 2023, and must not have an advanced degree in field relevant to the role/project Must be able to start in June or July 2026 and commit to the full one-year program, which will end on May 28, 2027 Must be authorized to work in the U.S. for the program duration Must be 18 years of age or older Prior coding experience in Python is preferred Prior experience with PyTorch and/or training neural networks is helpful Benefits Medical Dental Vision Basic life insurance 401k plan Paid time off Company Overview The Allen Institute is dedicated to answering some of the biggest questions in bioscience and accelerating research worldwide. It was founded in 2003, and is headquartered in Seattle, Washington, USA, with a workforce of 501-1000 employees. Its website is