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implementation of novel training strategies under experimental constraints, e.g., active learning and other data-efficient approaches Conduct large-scale benchmarking and comparative evaluation of gene
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We are seeking a Senior Researcher to join a joint research programme between the Big Data Institute (BDI) in the Nuffield Department of Population Health and the Centre for Human Genetics in
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developing next-generation AI methods for healthy climate adaptation. The position will focus on building and evaluating foundation models for large-scale spatiotemporal health and environmental data. Our team
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background in statistics, and familiarity with large data sets such as metabolomics or epigenetic sequencing. Experience in epigenetics or gene regulation is a plus. Experience with statistical analysis tools
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scientific discovery with a focus on microscopy image analysis. Specifically, we are interested in the development of new methods to identify structures of interest in large datasets (detection, segmentation
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this postdoc position, the focus is on methods and algorithms for large-scale graph analytics, in particular network science approaches for analyzing longitudinal, population-scale relational data derived from
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interpreting large datasets using statistical programming languages (e.g. R, Python etc.) Proven independent working style, technical problem solving, data analysis and generation of novel ideas Proficient
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, fluorescence lifetime and vibrational imaging methods. Large-scale and high-throughput imaging and analysis pipelines: data acquisition and analysis to characterize cell-types and connectivity in mammalian brain
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Fritz Haber Institute of the Max Planck Society, Berlin | Berlin, Berlin | Germany | about 5 hours ago
) beamline. The position offers the opportunity to play a leading role in designing and performing time-resolved experiments, analyzing spectroscopic data, and interpreting results in close collaboration with
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research experiments within the Pediatric Brain Tumor Research Program. This position will be responsible for evaluation and analyzing large sequencing and multiome data-sets. Baylor College of Medicine