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international network of collaborators and visitors. Further information: Department of Computer Science: https://www.science.ku.dk/english/about-the-faculty/organisation/ Faculty of Law: https://jura.ku.dk
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international team environment. Preferred Qualifications Demonstrated expertise in quantitative data analysis and statistical modeling. Experience working with large, complex, and multi-dimensional datasets
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healthcare applications. We use large real-world complex datasets, including data extracted from electronic health records and medical images, for applications pertaining to patient diagnostics and prognostics
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or perl) and experience working in Linux and/or high-performance cluster environments. • A strong ability to perform analytical reasoning to extract biological insights from data-driven approaches will be
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encourage applications from diverse candidates and are committed to creating an inclusive and supportive research environment. Job Responsibilities Data Analysis and Publication (70%) Manage and curate large
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. We are currently analyzing brain, CSF and blood, multi-omic data (transcriptomics, proteomics and metabolomics), from a large collection of well-characterized samples to identify novel biomarkers and
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spectroscopy of exoplanets, brown dwarfs, and young star clusters with the James Webb Space Telescope (JWST) are particularly encouraged to apply. Group members lead a Large and Long Program at the Gemini
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scattering for structure and dynamics of these systems. For more information, see https://www.soft-matter.uni-tuebingen.de . Currently we are looking for a post-doctoral researcher to perform state-of-art X
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primates or humans – Theoretical neuroscience, machine learning, or AI • Proficiency in Python, MATLAB, or equivalent data‑analysis frameworks. • A passion for big‑picture questions, open science, and
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analysis tools (e.g., 3D Slicer) Experience managing GPU-enabled cluster nodes Desirable: Experience working with current large language models (LLMs) and their ecosystems Required Application Materials