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will develop novel statistical and machine learning methods for any of the following: multi-omics data (such as bulk and large-scale single-cell RNA sequencing data, spatial transcriptomics, bulk and
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initiatives in blockchain data collection and management. The position focuses on developing innovative solutions for large-scale blockchain data analytics and management systems. Key Responsibilities Lead
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data. Publish research results in high impact journals. Collaborate with other UM6P researchers/groups on multidisciplinary research projects related to the field. Development and implementation
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series, research seminars, and workshops. Candidates will possess a PhD (or be close to completion) in any relevant area of Management. The successful candidate will have expertise in composing large
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, Computer Science, Statistics or a related field. Strong mathematical/scientific programming skills. Experience with bioinformatics algorithms and large-scale data analysis. Baylor College of Medicine is an Equal
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. Previous work experience in big data analysis, managing large databases of research projects relating to family caregivers of older adults and/or cost effectiveness evaluation, and with related track records
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn't imagine the future, we invent it. If you're passionate about joining a community that challenges the
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theoretical concepts with available data; Working with large databases (e.g. PATSTAT, ECOLEX, Web of Science); Quantitative time series analysis, including structural break detection and clustering techniques
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learning paradigms as well as interactive data- and model exploration with domain knowledge towards optimal performance in real-world generalization scenarios. AqQua is a large-scale collaborative research
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informed neural networks (PINN) and explainable machine learning (EML) frameworks; experience in related technologies including large-scale data analysis, deep learning, Python, PyTorch; and the ability