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related to engineering specialized metabolite biosynthetic pathways Essential and Other Functions: (40%) molecular biology and microbiology (50%) Data analysis (10%) Prepare manuscripts and communications
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-physiology-pharmacology/changiz-taghibiglou.php ) at the University of Saskatchewan (USask) in collaboration with Clinical Colleagues: Dr. Andrew Kirk (Div. Neurology, U of S), Dr. Ravi Nrusimhadevara (Dept
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journals - Presentations at conferences and to various stakeholders 5% PROFESSIONAL DEVELOPMENT -Contribute to researcher's own professional development, such as attending workshops, guest lecturing
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Nature Careers | Vancouver South Shaughnessy NW Oakridge NE Kerrisdale SE Arbutus Ridge, British Columbia | Canada | 8 days ago
tumor suppressor and complement inhibitor CSMD3. The successful candidate will join a dynamic and collaborative team dedicated to advancing the molecular understanding of cancer development and
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for applications. Applicants will be contacted by the department if they are being considered for an open position. Postdoctoral Associates conduct research or service that provides further development of career
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the project goals. The successful candidate will be working closely with the project PI’s to generate and test hypotheses, develop and run model simulations, and report findings through presentations
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Hours per Week 40 Full Time or Part Time? Full Time Shift Day Work Schedule Summary Monday – Friday 8-5 VP Area U of U Health - Academics Department 02171 - Education Program and Trainees Location Campus
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activities. The Sydney EarthBank node will join the national AuScope Geochemistry Network , an Australian consortium of Earth Science institutes cooperating to develop national geochemistry research
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and their application in animal models. There will be opportunities to lead a team of students, contribute to grant writing, engage in professional development, and disseminate results at conferences
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on applying, developing and implementing novel statistical and computational methods for integrative data analysis, causal inference, and machine/deep learning with GWAS/sequencing data and other types of omic