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analysing large and complex datasets, including multi-omics and perturbation-response data, with a strong emphasis on data quality, reproducibility, and biological interpretability. Practical experience in
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Solid programming skills, e.g., Python, machine learning frameworks, data analysis tools Experience with social media research or large language models is an advantage Strong analytical thinking and
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bioinformatics, computational biology, genomics, statistical genetics, or a related quantitative field, together with demonstrated expertise in large-scale genomic data analysis and significant experience in
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biostatistical methods to better personalize treatment of cancer patients from deep and diverse types of biomedical information. Analysis of large‑scale clinical, genomic, and molecular datasets. Development and
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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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of this programme. The profile PhD in computer vision, computational biology, physics or a related discipline Demonstrated expertise in image analysis and working with large-scale imaging datasets Strong expertise in
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learning analysis of biomedical data and bioscientific programming for projects on neurological diseases. The candidate should have experience in the analysis of large-scale biomedical data (omics, clinical
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researchers. The group conducts large-scale registry-based research covering all aspects of drug utilization, effectiveness, and safety, using Danish nationwide health registries as well as international data
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areas Prior experience in large-scale data processing and statistics / machine learning is required Previous work and publications in bioinformatics analysis of large-scale biomedical data, e.g., omics
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human health. Within this mission, the Jug Group develops advanced computational methods and open scientific software to extract knowledge from complex biological imaging data. We work at the intersection