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Academic Job Category Faculty Non Bargaining Job Title Postdoctoral Research Fellow in Machine Learning for Genomics, Transcriptomics, and Bioinformatics Department Bashashati Laboratory | School
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The University of British Columbia (UBC) | Vancouver UBC, British Columbia | Canada | about 1 month ago
for Genomics, Transcriptomics, and Bioinformatics Job Summary The School of Biomedical Engineering at the University of British Columbia, Vancouver campus is seeking one postdoctoral fellow to join our dynamic
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Academic Job Category Faculty Non Bargaining Job Title Postdoctoral Research Fellow in Machine Learning for Genomics, Transcriptomics, and Bioinformatics Department Bashashati Laboratory | School
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to develop deep learning models for analyzing whole-slide histopathology images, as well as natural language processing (NLP) methods for clinical records such as pathology reports and electronic health data
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Biology, Bioinformatics, Statistics, or a closely related discipline, and have an strong record of research productivity. The ideal candidate will have experience in deep learning, generative models
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documentation. Develops integrative models of radiation response through the combination of genotype and biomarker data. (Raman, blood marker etc.) Facilitates processes for data transfer and collaboration by
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researcher position under the supervision of Assistant Professor Dr. Anže Švara. This research will leverage advanced sequencing and bioinformatics analyses and will be conducted across field, greenhouse, and
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to develop deep learning models for analyzing whole-slide histopathology images, as well as natural language processing (NLP) methods for clinical records such as pathology reports and electronic health data
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record of publishing scientific papers in top journals as a lead author. Excellent communication skills (oral and written). Be able to work independently and meet deadlines. Bioinformatics experience is
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. The next key step is identifying sensors for many new metabolite and drug targets. Our goal is to use a range of novel in-house experimental methods to discover hundreds of new sensors and in parallel