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, protein structure modelling, AlphaFold/multimer-based analyses, statistics, data visualization, and interdisciplinary work at the interface of proteomics, structures and machine learning. Track 2
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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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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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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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excellence. Assisting in the mentorship of junior analytical staff members and graduate students QUALIFICATIONS A PhD in computational biology, bioinformatics, statistics, computer science (Machine Learning
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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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, 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
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Columbia (UBC) Vancouver campus invites applications for a full-time Postdoctoral Research Fellow with expertise in artificial intelligence (AI), machine learning (ML), and data science. The position will be
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with leading machine learning frameworks and modern AI environments, including multi-GPU model training and large-scale inference on dozens to hundreds GPUs, are required. Additional Qualifications