87 phd-agent-based-modelling Fellowship positions at University of British Columbia in Canada
Sort by
Refine Your Search
-
, policy, energy conversion, new business models, techno-economic and life cycle analyses, machine learning, optimization, AI, intelligent networks, among others. The PDF will join a project in collaboration
-
Citizenship Canadian Permanent Resident International Degree Level Doctoral The Google PhD Fellowship Program was created to recognize outstanding PhD graduate students doing exceptional work in computer
-
PostDoctoral Research Fellow and PHD positions - Global Pediatric Digital Health (Child Health, Epidemiology, data science, and/or digital health) SUMMARY We are seeking applications for a 2
-
functional genomics, CRISPR-based screening, or single-cell technologies. Hands-on experience with next-generation sequencing library prep and tissue culture models. Demonstrated ability to conduct independent
-
one postdoctoral fellow to join our dynamic team in the AI in Medicine Lab (www.aimlab.ca). This position is based in the School of Biomedical Engineering (SBME). The successful candidate will work
-
postdoctoral fellow to join our dynamic team in the AI in Medicine Lab (www.aimlab.ca). This position is based in the School of Biomedical Engineering. The successful candidate will work in the AI in Medicine
-
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
-
members on combinatorial CRISPR screen strategies for target credentialing in cancer models Computational analysis of screen data Design and execution of combinatorial target validation experiments in PDXO
-
-cell compartment, develops and deteriorates with age, and how these processes can be understood, modeled, and ultimately reversed or rebuilt using bioengineering and synthetic biology approaches
-
, and interpreting models, Analyzing genetics data (e.g. GWAS, eQTLs), including predicting variant effects, stratifying patients, identifying desired patients for recall, Designing, synthesizing, and