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Field
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for a Research Fellow in Bioinformatics/Computational Biology to help develop, coordinate, and conduct robust analysis of high-throughput host protein data under supervision using advanced analytical and
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immediately on arrival. IOI, part of the Mathematical, Physical and Life Sciences Division, has access to world class expertise and resources in infection biology, organic and medicinal chemistry, pharmacology
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(for Research Fellow) or equivalent experience in bioinformatics, computational biology, statistics, genetics or a related field Demonstrated experience in transcriptomic data analysis and relevant bioinformatic
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direction from the assigned supervisor. Supervision Given None. Required Education Doctoral degree in Cancer or Molecular Biology, Genetics, Drug delivery, Bioinformatics, Biostatistics, Computational Biology
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, Genomics, or a related field such as Computer Science, Biomedical Sciences, Molecular and Cellular Biology, or Cell Biology, with demonstrated computational expertise. Individuals with background in physical
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fast-readout electron detectors to validate the methods developed. The successful candidate will have a PhD in Physics, Materials Engineering, Computer Science or a closely related field. Research
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understood, modeled, and ultimately reversed or rebuilt using bioengineering and synthetic biology approaches. The successful candidate will: Investigate mechanisms of T-cell development, aging, and thymic
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Human Program and UBC’s Biodevice Foundry. Qualifications PhD in immunology, developmental biology (focused on the immune system), immune-engineering, or a related field (obtained within the last 5 years
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with strong international reputations and a track record of extramural support. Faculty research interests are focused in cellular, molecular and integrative biology, reproductive biology including
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the application form, which is limited in the number of characters it will allow.) Interviews: 4th and 5th of August 2025. About you The successful candidate must hold a PhD in mathematics or computational biology