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fields (data science, bioinformatics, health informatics, computer science, information systems, statistics, public health, biological sciences, microbiology, or a related field). Degree must have been
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/biomedical innovation, Bioinformatics, Computational Biology, or a related field. An established record of high-quality research applying AI/ML, computational, data-intensive or related approaches to medical
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-purposing opportunities. This position will be especially suited to candidates with interest in functional genomics, bioinformatics, lung cell biology and respiratory medicine. The successful candidate will
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, MD/PhD, or MD) in computational biology, bioinformatics, biostatistics, cardiovascular biology, epidemiology, or a closely related field Experience with proteomic, metabolomic, or other omic data
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The Duke-NUS Centre for Biomedical Data Science (CBDS) serves as a central hub for Duke-NUS faculty specialising in Biostatistics, Bioinformatics, Systems Biology, Artificial Intelligence (AI), and
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) or bioinformatics with good understanding of biochemistry (subprojects 2,5,9) Proven prior knowledge in hub molecule relevant topics A high level of motivation and interest for topics of HubMOL High-level of
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these interactions. This track is particularly suited for candidates with a PhD in bioinformatics, structural biology, computational biology or a related field, and experience in computational structural biology
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for purposes of collective bargaining and matters affecting your compensation and working conditions. Basic Qualifications PhD in Computational Biology, Bioinformatics, Machine Learning, Data Science, or a
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bargaining and matters affecting your compensation and working conditions. Basic Qualifications Ph.D. in neuroscience, molecular biology, genetics, bioinformatics, or a related field.Strong background in
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– from ecosystems to microbiology and developmental biology, from evolution to cell biology, from molecular biology to systems biology, bioinformatics, and genomics. It is always an exciting time for