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Field
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to applicants with demonstrated expertise in energy systems analysis, in the collection, processing, and integration of country-specific data for economy-wide energy system decarbonization models, in
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Knowledge, Skills & Abilities: • Knowledge of synthesis of Pyridinophane Macrocycles. • Knowledge of and experience with molecular modeling. • Knowledge of and expertise in data analysis and work-up
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)-statistics, (applied) mathematics, or a related STEM field. Prior working experience with EHR data, machine learning, NLP, bioinformatics, and large language models (LLM) is preferred. In particular
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Laboratory (ORNL) is seeking several qualified applicants for postdoctoral positions related to Computational Methods for Data Reduction. Topics include data compression and reconstruction, data movement
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, including applied mathematics and computer science, experimental computing systems, scalable algorithms and systems, artificial intelligence and machine learning, data management, workflow systems, analysis
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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equivalent) in hand by December 2025. Related research experience in atmospheric observation and data analyses. Preferred Qualifications: Ph.D. (or foreign equivalent) in Atmospheric Sciences, Engineering
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to submitting your application, please review and update (if necessary) the information in your candidate profile as it will transfer to your application. Job Title: Post Doctoral Scholar Department: Engineering
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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