Allen Institute · 3 weeks ago
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.
Neuroscience
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
Qualification
Required
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
Preferred
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
Allen Institute
The Allen Institute is dedicated to answering some of the biggest questions in bioscience and accelerating research worldwide.
Funding
Current Stage
Late StageRecent News
2025-12-25
2025-12-24
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