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Field
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We are seeking a Research Fellow - Data Science professional with strong expertise in machine learning, deep learning and high-frequency physiological signal analysis. This is a unique opportunity to
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completion must be in hand on or before the start date Strong programming and computational skills Experience with statistical modeling, machine learning, or large-scale data analysis Desired Qualifications
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, Bioconductor, tidyverse, SingleCellExperiment, or related software. Experience with Python and machine learning approaches is considered an asset. APPLICATION PROCEDURE Applicants should submit: Cover letter
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researcher in Computer Science, Data Science, Human-Computer Interaction, Psychology, Empirical Educational Research, Learning Sciences, Cognitive Science, or related disciplines who is eager to contribute
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dataset analysis, machine learning tools, and relevant computational biology approaches • Document, compile, and format data analysis in presentations and reports to supervisor. • Mentors and trains
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neurocritical care research The Opportunity We are seeking a Research Fellow - Data Science professional with strong expertise in machine learning, deep learning and high-frequency physiological signal analysis
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Experience analysing large datasets and applying data-cleaning techniques along with performing statistical analyses leading to the understanding of the structure of datasets Machine Learning & AI: Train
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the assembly, management, and analysis of complex datasets, including the application of machine learning techniques to develop a range of models such as predictive and image-recognition models. A key aspect of
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present work-in-progress to PhD students, postdoctoral fellows, faculty, and other members of the Korbel Community. Further, they will benefit from the support and collegiality of the large Korbel faculty
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, responsible AI, digital health and global maternal and child health. The work will include development and application of machine learning and AI methods to large-scale, longitudinal, routinely collected