14 Engineering "https:" "https:" "FORTH" positions at Nature Careers in United States
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converted to the currency of that country. Springer Nature is an Equal Opportunity Employer that complies with the laws and regulations set forth in the following https://www.eeoc.gov/sites/default/files/2023
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interdisciplinary project. The opportunity to engage with world-class researchers, software engineers, and AI/ML experts, contribute to impactful science, and be part of a dynamic community committed to advancing
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the laws and regulations set forth in the following https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf poster. At Springer Nature, our mission is to be part of
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applications are encouraged. US Hourly Pay is $22.00 per hour. Springer Nature is an Equal Opportunity Employer that complies with the laws and regulations set forth in the following https://www.eeoc.gov/sites
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countries when converted to the currency of that country. Springer Nature is an Equal Opportunity Employer that complies with the laws and regulations set forth in the following https://www.eeoc.gov/sites
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Card’s lab at the Mortimer B. Zuckerman Institute at Columbia University seeks a creative, experienced, independent Mechanical Engineer to support groundbreaking research in the neural circuits underlying
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skilled Data Engineer to drive scientific innovation through robust data infrastructure, model training, and inference systems. You'll design, develop, and optimize scalable data pipelines and build multi
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The laboratory of Professor Tirin Moore at Stanford University is seeking a Software Engineer. The Moore lab seeks to understand the neural circuits underlying fundamental perceptual and cognitive
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outstanding opportunity for an optical engineering-focused Postdoctoral Scientist to join the lab team of Dr. Cristina Rodriguez, Freeman Hrabowski Scholar , based in the Department of Biomedical Engineering at
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skilled Data Engineer to drive scientific innovation through robust data infrastructure. You'll build a large-scale foundational microscopy image dataset and develop scalable data processing pipelines