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-temporal overlaps in the presence of both human and marine mammal activities. By using sighting data and ship positional data, as well as passive acoustic recordings, the project will provide an overview
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design. The successful candidate will carry out both independent and team research within a collaborative partnership between UNSW and the fusion energy company HB-11 Energy. This position supports a
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moves. Success will be measured by having published or contributed to papers in top venues (e.g., Nature Science of Learning, Computers and Education, ACM Learning at Scale, Educational Data Mining) and
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of agricultural in dry lands and marginal environments, animal value chain, water and energy sustainability, biorefinery and bioenergy, cultivation and conversion of micro and macroalgae, and geology and mining
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of agricultural in dry lands and marginal environments, animal value chain, water and energy sustainability, biorefinery and bioenergy, cultivation and conversion of micro and macroalgae, and geology and mining
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The place of work is Aarhus University, Campus Ole Worms Alle 3, 8000, Aarhus C. The affiliation will be with Land-CRAFT, Department of Agroecology. More information can be obtained from Assistant Professor
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The place of work is Aarhus University, Campus Ole Worms Alle 3, 8000, Aarhus C. The affiliation will be with Land-CRAFT, Department of Agroecology. More information can be obtained from Assistant Professor
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, modeling and analysis, integrating diverse data sets to identify global risks affecting sourcing strategies. In this role you will: Conduct and contribute to research and model development to enhance
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 16 hours ago
Posting Information Posting Details Department Neurology - 411801 Posting Open Date 05/16/2025 Application Deadline Open Until Filled Yes Position Type Postdoctoral Scholar Position Title Post-Doc
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weather instrumentation data analysis (lidar, radar, weather station, radiometer, sonde, cameras) Experience with mining and cleaning “big” observational data and/or online databases Experience with