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cause. We are also interested in genetic interactions (epistasis), tandem repeats, machine learning, and other areas of AD research that have not yet been explored extensively. You will be part of a
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managing and curating large datasets and with machine learning techniques preferred. Excellent oral and written communication skills and the ability to perform both self-directed and guided research
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large scale flow network simulations, machine learning, and methods from topological data analysis, to a broad set of problems. Examples include modeling vertebrate and invertebrate circulatory systems
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novel biomarkers by integrating proteomics, metabolomics, and genomics / transcriptomics data with machine learning techniques. The position is to be filled starting November 1, 2025, either full-time or
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of manufacturing. We have identified an opportunity to combine continuous microfluidic (µF) process models, process analytical technology (PAT) and machine learning (ML) to achieve a paradigm shift in bioprocess
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within the role to pursue an independent research project in the general remit of gene expression and the lab. Candidates with interest or experience in machine learning, artificial intelligence and
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or translational research experience Knowledge of machine learning, Bayesian modeling, or statistical method development Ideal Personal Attributes: Independent, proactive, and scientifically curious Detail-oriented
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image analysis Ability to do original and outstanding research in computational biology, and expertise in computational methods, data analysis, software and algorithm development, modeling machine
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, and expertise in computational methods, data analysis, software and algorithm development, modeling machine learning, and scientific simulation Ability to work well in an interdisciplinary environment
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Ability to do original and outstanding research in computational biology, and expertise in computational methods, data analysis, software and algorithm development, modeling machine learning, and scientific