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. transformer models). One focus of this work will be on B-cell receptor evolution. Experience in applications of modern machine learning methods as well as in biological data analysis are needed for the position
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | about 1 month 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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Engineering, Mathematics, Statistics, Computer Science or conjugate subject and have a strong record of publication in the relevant literature. Good knowledge of machine learning algorithms is essential, as
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, finance or computing science/natural language processing/machine learning. Preference will be given to those who are proficient in Python, adept at processing large-scale data and have worked with large
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machine learning models directly on these edge devices for real-time anomaly detection and identification. You will develop robust signal acquisition and processing pipelines, translate research-grade
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of the following: cancer biology / cancer immunology / epithelial cell biology / evolutionary biology / genomics / statistics / mathematics or machine learning* Technical qualifications: For bench
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users, thanks to the use of machine learning tools and techno-economic analyses. This project is aligned with the sustainable development goals (SDG) 7 and 10 of the United Nations, by promoting a low
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on studying the principles of neural computation through recurrent neural networks, dynamical systems theory, and machine learning. - Develop mathematical and computational models of neural networks - Analyze
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with numerical modeling, energy system optimization and possibly machine learning to guide energy transitions towards net-zero systems. The research supervisors have prepared multiple potential projects
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: Preferably PhD degree in Computer Science or equivalent. Have a solid foundation in the following areas: Computer Vision, 3D vision; Strong publication records in top-tier computer vision and machine learning