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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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, 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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, 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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area of expertise. Collaboration will involve joint problem-solving, the integration of data streams, and the development of decision-support tools to inform large-scale restoration policy. Your profile
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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
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analytical methods to large data sets The possibility for contract extension Flexibility in planning working hours Advanced professional training opportunities Possibility of participation in international
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of cellular aging, resilience, and fibrosis. Responsibilities Develop and implement analytical pipelines for large-scale single-cell, spatial, and multi-omics data integration Build and apply machine learning
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Experience with writing scientific publications Experience in working with contaminants like PFAS, PCBs and mercury, fatty acids, stable isotopes and modelling in R A talent for working with large data sets
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environment focusing on integrating multi-source satellite remote sensing data and developing novel algorithms to quantify agroecosystem variables for environmental sustainability. You will focus on processing
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and applying genetic and genomic approaches to biodiversity research. This includes integrating environmental DNA (eDNA) and molecular tools with ecological data to enhance our ability to assess