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Field
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experiences in at least one of the following areas: 1) advanced data analytics for performance prediction and risk analysis of transportation infrastructure; 2) network level optimization for transportation
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students, interact with collaborators, and adopt and optimize relevant techniques for the project where applicable. Professional development: 5% Requirements PhD in molecular biology, cancer biology
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experiment, as well as in the commissioning, optimization, and development of analyses for the ALPHA experiment. The candidate is also expected to take a leadership role in JHU-based testing toward
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, biochemical assays, testing with pharmacological compounds and mouse models. The postdoc will write manuscripts, mentor students, interact with collaborators, and adopt and optimize relevant techniques
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digestion), and should have documented capabilities using a variety of simulation and optimization techniques. Familiarity with electric power grids and rate structures is highly valued, as is experience with
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or Oropouche viruses). Other projects include improving risk assessment, optimizing surveillance system design, and developing and evaluating mitigation strategies. These projects aim to integrate epidemiology
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algorithms for the scanner using machine learning and deep learning. Qualifications: The position requires some background in machine learning, optimization, and deep learning. Some familiarity with MR physics
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areas Biomedical applications, social determinants of health or other demographic health areas Spatial microsimulation, spatially weighted regression, combinatorial optimization or Bayesian network
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 6 hours ago
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 the nation’s leading
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including the integration of large-scale human genome-wide association (GWAS) with bulk and single-cell (e.g. scRNA-seq and scATAC-seq) sequencing, optimization of in-vitro and in-vivo exposure protocols, and