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at Cornell University, but the project will include close collaboration with colleagues at Penn State and MIT, as well as a machine learning-focused geothermal start-up (Strabo Analytics). The entire project
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interested in candidates who can leverage machine, deep learning, and statistical methods to monitor species distributions and integrate biodiversity records from multimodal data sources to understand
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analyses using Danish register data and/or large genetic datasets. This may include genetic analyses, causal inference, epidemiological analyses, and clinical prediction modelling using machine learning
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on these projects, including Pawan Sinha at MIT, Alireza Ramezani at Northeastern, Joo-Hyun Song at Brown University, and David Lin at Massachusetts General Hospital. The research is supported by the National
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of this project is to add support for automatic code optimization in Tiramisu. In particular, we want to use machine learning/deep learning to achieve this. Currently, a basic automatic optimization module
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(Helsinki Institute of Life Science, University of Helsinki) is looking for a postdoctoral researcher with background in neural network models . Our group develops computational models, machine learning and
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an apéro A workshop organized by Heather Kulik, associate professor at MIT. Leading researchers discuss recent advances and outstanding challenges in applying state-of-the-art machine learning algorithms