18 parallel-computing-numerical-methods-"DTU" Postdoctoral positions at University of South Carolina in United States
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the research program. Use synthetic organic chemistry methods to develop and optimize fluorescent indicators and organelle-targeting ligands. Essential Function Yes Percentage of Time 35 Job Duty Design
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, the individual will assist our research program, which examines the protein functions in neurons using Proteomics, AAV, and CRISPR genome editing approaches. Responsibilities will include assisting with primary
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parallel/GPU computing. Job Duties Job Duty Doing research problems in the area of mathematical foundations of data science and machine learning. The postdoc will assist with ongoing research projects
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relevant programming languages. Ability to use/learn several advanced modeling methods (e.g., statistical, mathematical, individual-based, or machine learning models). Experience with high-performance
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to the advancement of knowledge in soil health and biogeochemical cycling. Applying appropriate statistical and computational methods to analyze experimental data, synthesizing results into coherent narratives, and
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will provide training in mixed-methods research, qualitative analysis, the science of patient engagement in research, and patient-centered outcomes research. Key responsibilities include designing and
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application. This is needed for comparison with the existing quantum dynamics methods and studies of new chemical systems. This is done on USC and group research computers. Essential Function Yes Percentage of
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chemistry, biochemistry, molecular biology, or a closely related field with specific expertise in metal homeostasis. This expertise could have been gained during the normal course of a doctoral degree program
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, implementing, and evaluating a community outreach STEM program for Columbia, SC participants. Job Related Minimum Required Education and Experience Requires a Doctoral (Ph.D.) degree in area of research
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students, and about 200 undergraduate majors. Faculty research interests include algebra, algebraic geometry, analysis, applied and computational mathematics, constructive approximation, data science