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-9820. Department: Research Agronomy Department's Website: https://crop-soil-environmental-sciences.uark.edu/ Summary of Job Duties: The Research Agronomy Program at the University of Arkansas Division
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. This position is designed for scientists with strong computational and quantitative training who are interested in agent-based modeling, network science, infectious disease dynamics, uncertainty quantification
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. transient laser spectroscopy), organic synthesis, and electrochemistry. Responsibilities: ● Performs research and/or development in collaboration with others ● Optimize and investigate new methods and
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profiling, molecular biology, cancer genomics, and in vivo preclinical modeling. Examples of representative recent papers led by wet-lab scientists in our lab (as first author) include: https://www.nature.com
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 14 days ago
the School’s Strategic Plan (https://pharmacy.unc.edu/about/oe/strategic-plan/). Our Vision is to be the global leader in pharmacy and pharmaceutical sciences. Our Mission is to prepare leaders and innovators
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 14 days ago
and World Report. The School has experienced unprecedented growth and success and continues to strategically position itself for sustained impact, as articulated in the School’s Strategic Plan (https
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for machine learning, generative AI, data analytics, and intelligent decision-making, while advancing the theoretical foundations of quantum-enhanced learning systems. Quantum Algorithms for Optimization and
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-deposited oxide films, and covalent or electrostatic functionalization (30%); 3. Build and optimize experimental hardware, including optical excitation and collection paths, microwave and RF delivery (30%); 4
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, pneumonia, and tuberculosis. Functional/ mechanistic validation of regulatory elements and gene networks controlling inflammation, immune memory, and tissue repair will be implemented using CRISPR inhibition
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methods with optimization and decision-support models. Background in one or more of the following: time-series analysis, neural networks, forecasting, uncertainty quantification, sensitivity analysis