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Field
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and assessment of current and proposed education programs. Collect, prepare, and analyze research data; maintain a computer database of research data; tabulate and display data for presentation in
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understanding of adaptive immune receptor (antibody and T-cell receptor) specificity using high-throughput experimental and computational immunology combined with machine learning. The long-term aim is to
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statistical methods for high-dimensional omics data, including multi-level data (subject, tissue, single-cell) with or without spatial features. • Data Analysis: Analyse large-scale omics datasets, interpret
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, physics, artificial intelligence, machine learning, topological data analysis, and statistics. We are interested in analyzing big data of complex systems such as DNA, RNA, biological networks, social
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technology. Key Responsibilities: Collaborate with partners from both the academia and the industry to lead and/or conduct innovative research on, but not limited to transfer learning, explainable machine
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processing. We have therefore taken the decision to prioritise processing complete applications. Applications that fail to include important documents or information, or that diverge substantially from our
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You Completion (level A and B) or near completion (level A) of a PhD in the field of Information Retrieval, Natural Language Processing, or Machine Learning on Textual Data. Demonstrated expert
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Computer Science or a related field Proven ability to conduct independent research with a relevant publication record Outstanding data analytics, mathematical, and computer modelling skills Excellent interpersonal
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Postdoctoral Fellow with Assistant Professor Tracy Ke. Assistant Professor Ke’s lab focuses on research in high-dimensional data analysis, machine learning, social network analysis, text mining, bioinformatics