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be developed and implemented in the GEOS-Chem chemical transport model, coupled to the Community Earth System Model. Standardized large wildfire events will be simulated based on historical data and
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utilizes the world-class Danish registries as well as international data sources to assess pharmacological questions in large populations. The environmental medicine group studies the impact of early life
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Postdoc position to support international research and capacity-building projects employing elect...
of large-scale EM data for groundwater mapping. Teaching and training of Ethiopian partners and students in EM methods, data processing workflows, inversion software, and geological interpretation
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addition to the large base of basic research, the center has a large number of ongoing industrial projects and partnerships. In the Valero lab, we offer a dynamic, social and interdisciplinary scientific environment with
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quality and functioning, particularly in plumes near river outlets. This post doc project will rely on existing data as well as new field data of nutrients, carbon, and stable isotopes from riverine-coast
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, handling, and synthesising big data geospatial data sets from various data sources. Cutting-edge expertise in advanced statistical analyses of large data sets and strong knowledge of programming languages
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assessments. Key responsibilities Design and conduct experiments. Operate and maintain gas measurement equipment and flux chambers. Process, analyze, and visualize large data sets using Matlab, R, Python
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further information are invited to contact Associate Professor Niculina Musat (niculina.musat@bio.au.dk). Who we are The successful candidate will be employed by the Department of Biology at Aarhus
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, combined with advances in automation, analytics and data science, has fundamentally changed the scope and ambition of harnessing the potential of biological systems. Big data approaches and analysis
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Post Doctoral Researcher in Human-centred Large Language Models for Software Engineering, Departm...
. Required qualifications: A Ph.D. degree in Computer Science, Data Science, Software Engineering or related field. Solid research experience with using Large Language Models. Solid programming expertise in