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simulation in hydrogen production systems. They are expected to contribute to model development, analyze flow behavior, and evaluate the impact of operating conditions on hydrogen production. Strong
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, refining, separation, process optimization, and simulation. The postdoctoral researcher will be supervised by Drs. Junli Liu and Nathan Mosier. Interested candidates should submit an application containing a
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | 2 months ago
USNH Employees should apply within Workday through the Jobs Hub app The research position is within the broad area of biophysics, structural modeling, and molecular dynamics (MD) simulations
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functional assays such as cytotoxicity assays, ELISPOT, ELISA and cytokine release assays. Design and execute experiments in mouse models and assess efficacy of therapeutics. Perform histological analysis
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models. This theoretical project will facilitate close collaboration with experimental groups and enable benchmarking of theoretical predictions. The PhD researcher will be part of the Correlated Quantum
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models at many scales including electron dynamics, soft-matter physics, materials-biomolecules interaction and device physics exploiting the collaboration with a multidisciplinary team of theoreticians and
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following areas: Salmon ecology (including biophysical ecology, modeling, acoustic telemetry, and landscape and seascape ecology) Fisheries assessment (including habitat and groundfish ecology and assessment
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Computing (e.g., memristor modeling/simulation/manufacturing) and Edge AI related areas (e.g., AI algorithms, AI accelerator, VLSI). Detailed Position Information The Department of Electrical and Computer
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mixed research methods—including behavioural surveys, environmental monitoring, and dynamic thermal modelling—the project aims to generate retrofit strategies that improve energy efficiency, reduce carbon
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experiments; supporting other group members with data analysis and interpretation from both simulations and experimental data; and use the developed framework to design new materials with optimised performance