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Field
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quantum information science. Specific topics of interest include dynamics in closed and open quantum systems, digital and analog quantum simulation with quantum computers or atomic-physics platforms, and
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 7 hours ago
USNH Employees should apply within Workday through the Jobs Hub app The Global Ecology group at the Earth Systems Research Center, University of New Hampshire (UNH), has an immediate opening for a postdoctoral research associate. The goal of this project is to advance understanding of how...
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Extensive knowledge of Microsoft Excel and good computer programming skills Knowledge of techno-economic analysis and life cycle analysis Experience working with Argonne’s EverBatt model, GREET model, and
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Computer Science or related fields Experience in power system modeling, optimization, and control Experience in at least one of the power system software tools including OpenDSS, PSCAD, PSS/E Experience in at least
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, faculty members, researchers, and students are revolutionizing focus areas in advanced manufacturing, bioengineering, computational engineering, energy and the environment, product design, and robotics. In
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contribute to open-source code repositories and documentation. Position Requirements Required skills, knowledge and qualifications: PhD in physical oceanography, coastal engineering, computational science
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-rated accordingly. The University also offers a comprehensive benefit program to eligible employees. Please see this link for more information.
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. Familiarity with computational modeling of structure-function relationship Experience in identifying metabolites in biological samples. Sufficient knowledge in statistical analysis tools (e.g., SAS, R, XLstat
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the fields of cancer survivorship, genetics, stem cell pharmacogenomics, epidemiology, biostatistics, and computational biology. The successful applicant will gain extensive training and experience in genetic
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such as Simcyp, PK-Sim, or similar tools Strong quantitative and computational skills, including proficiency in R Demonstrated ability to analyze and interpret pharmacokinetic data Strong written and verbal