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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 8 hours ago
environment. The full job description is available, here: https://drive.google.com/file/d/14vuatOC6NKg9w4j91r_Zb6KF8lTxUoe5/view?usp=sharing Job Requirements REQUIRED: A PhD in neuroscience, computer
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(SHORES) and the Division of Engineering, New York University Abu Dhabi, seek to recruit a Postdoctoral Associate to work on a fascinating project focused on the development machine-learning powered digital
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research facilities, and high-performance computing resources. Education Requirement: - MBBS, MBBCh, MS, MD, PhD, or MD/PhD in Radiology, Medical Physics, Biomedical Engineering, Computer Science, or a
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or junior graduate students. A formal training, education, or certification in a secondary area (beyond the main PhD focus) such as additive manufacturing, advanced/hybrid manufacturing, machine learning
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is located in Pittsburgh, PA, a city with a vibrant research and tech community. The ideal candidate has a PhD in Computer Science, Electrical Engineering , or a related field, with a strong
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, Computer Supported Cooperative Work, Ubiquitous and Pervasive Computing and related topics. Our section is one of top research environments that bridges technology, theory, and empirical studies. We
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Employer https://main.hercjobs.org/jobs/22167044/post-doctoral-associate-in-the-division-of-engineering-x28-electrical-and-computer-engineering-x29-dr-qurrat-ul-ain-nadeem Return to Search Results
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*• Experience in Python or another programming language (projects, GitHub repositories, courses, scientific use).• Training or experience in machine learning and data science applied to environmental or energy
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 25 days ago
data analysis methods to study biological memory circuits and their applications to machine learning. Building on recent work from the Fiete Lab, the role focuses on identifying principles of biological
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quantitative and machine learning approaches ● Developing predictive models linking nuclear features to future cell fate ● Interacting with collaborators in imaging, computational biology, and developmental