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-of-the-art sparse algorithm in matrices, tensor and networks for large-scale numerical, scientific and AI models and disseminating findings through publications and presentations in top-tier peer-reviewed
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | about 1 month ago
will develop detailed lifecycle assessments and technoeconomic analyses of the pyrolysis process and for large-scale end-uses of the co-produced solid carbon. The geologic hydrogen project will develop
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sciences and energy; social sciences; arts and humanities; and computer and information sciences. The Research Foundation, a private, not-for-profit corporation, is an employer separate from both SUNY and
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and brain that explain vision loss, building on our previously-developed method linking clinical, neural and behavioral data (Allen et al., 2018; Miller et al., 2019; Pedersini et al., 2023). We combine
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qualification in Genetics, Bioinformatics, Computer science, Data science, Statistical Genomics or a related discipline involving the interrogation of ‘omics’ datasets. Hands-on experience with large-scale human
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Requisition Details GENERAL REQUISITION INFORMATION EEO Statement: UNMC is an Equal Employment Opportunity Employer, including an equal opportunity employer of protected veterans and individuals
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. The successful candidate will join the Experimental High Energy Physics group led by Profs. Brinkerhoff, Dittmann, Hatakeyama, and Wilson to participate in the Compact Muon Solenoid (CMS) experiment at the Large
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, developing research proposals, and helping with graduate student mentoring and group organization. Opportunties to Contribute Analyze and interpret data to support collaborative discussions and decision-making
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for interacting with colleagues and stakeholders. Department Specifics: Develop various machine learning and data mining models including convolutional neural networks (CNNs), Transformers, large language models
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experience with AI model development, including fine-tuning, applying and evaluating large language models for tasks such as information extraction, summarization, and other biomedical or clinical applications