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Field
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Experiment (AGAGE) and a large atmospheric chemistry group at MIT. The work will focus on interpretation of AGAGE observations of greenhouse and ozone-depleting gases using models, measurements, and inverse
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technologies, including big data analytics, artificial intelligence (AI), remote data transfer, and cloud computing to help solve complex agricultural problems. -The candidate will work on the synthesis
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 13 hours ago
combination of observational data, machine learning techniques, and cosmological simulations. The group is actively involved in multiple JWST Guaranteed Time Observation (GTO) and General Observer (GO) programs
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strategies. The candidate will join the Machine Intelligence Group for the Betterment of Health and the Environment (MIGHTE) led by Prof. Mauricio Santillana. MINIMUM QUALIFICATIONS PhD in a quantitative field
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with computational scientists to integrate and interpret large-scale genomics data. Present research findings in lab meetings, departmental seminars, and conferences; prepare manuscripts and fellowships
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Pharmacology, the Clinical and Translational Science Institute and the McKnight Brain Institute, all of which provide state-of-the-art environments and large data sets access. Expected Salary: $62,232 annually
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candidate with expertise in the following four areas: (1) working with large-scale digital trace data; (2) building and running natural language processing and machine learning workflows; (3) experimental
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position. Applicants should have a PhD degree (or expect to receive a PhD degree by June 15, 2025) in Psychology or allied fields (e.g., Sociology) with an interest in conducting research relevant to racial
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several areas of ongoing research in the laboratory, including the isolation and genomic analysis of large DNA viruses, cultivation of diverse hosts, analysis of evolutionary relationships and genomic
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strongly recommended Other Requirements: May have to work on the weekend and/or after normal hours. May travel as required. Qualifications Required Education and Experience • Appropriate PhD in a Sport