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collisions applied to Large Hadron Collider (LHC) and/or the Electron-Ion Collider (EIC) and experimental data analysis with ALICE (A Large Ion Collider Experiment) or Stellar Intensity Interferometry (SII) in
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) to large-scale biomedical datasets. These models will be used to work with different types of data from the healthcare and biological domains, including genomic profiles, and clinical event sequences
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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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approaches for connectomics datasets. The lab develops computational approaches to reconstruct, analyze, and model large-scale connectomes, aiming to uncover organizational principles of neuronal circuits and
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microbial influences on fire ant behavior - Collect, analyze, and archive research data; establish and maintain databases; and utilize computational tools for data analysis - Perform experiments to evaluate
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capabilities o Demonstrated experience with machine learning and/or statistical modeling o Expertise in handling large-scale, complex datasets with strong data wrangling skills o Strong publication record
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data assets, and in the context of the world’s largest longitudinal population studies, many hosted here at the Big Data Institute, as well as other international initiatives. To be considered, you must
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analysis with AI. Position Specific Responsibilities/activities: Research and development relevant to ML, AI and big data analytics. Applications of advanced technologies in cybersecurity, anomaly detection
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evaluated on downstream tasks in recognition, segmentation, translation and retrieval. You will work with large multilingual datasets as well as unique Swedish sign language data through our collaboration
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experience in analysis of large datasets to examine pre- and post-diagnosis healthcare utilisation among patients with cancer in Luxembourg using insurance claims data. The researcher will be also working