82 engineering-computation-"https:"-"https:"-"https:"-"https:"-"U.S" positions at HHMI
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pioneering research center in Ashburn, Virginia, where scientists pursue fundamental questions in the life sciences. Our integrated teams of biologists, computational scientists, and tool-builders innovate
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to Janelia from the Washington D.C. metro area. What you’ll do: Lead the engineering architecture and development of next-generation FlyMAX systems, integrating robotics, computer vision, and AI-driven control
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pioneering research center in Ashburn, Virginia, where scientists pursue fundamental questions in the life sciences. Our integrated teams of biologists, computational scientists, and tool-builders innovate
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engineering. The position aims at developing qualifications and experience in computational research and professional software engineering in a research environment that enables the candidate to pursue
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the life sciences. The Technology & Systems Management (TSM) team enables that mission by delivering secure, reliable, and forward-looking enterprise technology capabilities across a complex, distributed
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discoveries and broader neuroscience insights. Assist with lab management, organization, equipment maintenance, and safety compliance. What You Bring Bachelor’s degree in computer science, engineering
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of your cover letter. About the role: The CombinAItorial Sensor Design project is part of HHMI’s AI for Science Initiative (ai.hhmi.org ) and brings together expertise in protein engineering, advanced
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are making a difference. Summary: The Howard Hughes Medical Institute (HHMI) seeks an academic scientist interested in an outstanding professional opportunity to serve as a Senior Director – Scientific Program
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multidisciplinary teams of computational and experimental scientists to define and implement best practices in data engineering, ensuring data quality, accessibility, and reproducibility. You'll maintain detailed
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pipeline for learning from a large-scale microscopy dataset. You will work with expert computational scientists, data engineers, and experimentalists to train models that learn foundational embeddings