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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
, and create personal and professional sustainability. We optimize our partnership with the UNC Health System through close collaboration and commitment to service. OUR VISION Our vision is to be
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design of hyperstable miniprotein binders using advanced computational platforms. The work integrates protein modeling, in silico affinity optimization, and mechanistic studies aimed at modulating key
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optimally interact with a varied population of diverse audiences. We are looking for someone who shares our values and who will support the mission of the university through their work. Qualifications: PhD in
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the development and testing of new materials. The work will involve reactor design and setup with gas flow capability and process optimization. Qualified candidates should have a Ph.D. in chemistry, physics
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the current state of knowledge on specific drugs’ PK and PD properties and on state-of-the-art approaches for study design optimization, dose individualization, and PK/PD modeling and simulation. Frequent
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the optimization of High- Throughput RNASeq capabilties. The successful candidate will help design and execute next- generation RNASeq experiments with the goal of significantly reducing the cost and increasing
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external) provides algorithmic and data-driven solutions providing fairer access to public educational resources. The lab enables school districts to optimize large-scale equitable resource allocation
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modeling. 80% research - The project focuses on developing theoretical models using optimization and information theory to improve understanding of plant hydraulic regulation at the leaf, plant, and
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optimization. We are particularly interested in a) developing novel AI methods for analyzing pathology data, b) multimodal data fusion strategies, c) development of computational methods for rare diseases and
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protocols of interest are 61, 62 (bioburden testing), 71 (sterility testing), and 85 (bacterial endotoxin testing). The researchers will be asked to optimize lab-specific protocols and run the protocols at a