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Field
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knowledge of the Boltzmann and quantum Boltzmann equation as well as stimulated Brillouin and Raman scattering. General: Knowledge of scientific programming language(s) and computer simulation
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of scientific programming language(s), computer simulation, and quantum computing algorithms All tasks and job responsibilities must be performed safely without injury to self or others in compliance with System
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; and crime and fire statistics for the three previous calendar years. A paper copy of the ASFSR is available upon request by contacting the UCSC Police Department at 114 Carriage House Rd., Santa Cruz
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
: Expertise in rare event simulation, deep learning, and developing computationally efficient approaches for simulation and modeling in complex systems is highly desirable Experience with parallel computing
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or similar), demand modeling software (e.g., TransCAD, Cube, Visum) meso- and micro-scopic simulation (Vissim, SUMO, Synchro), Geographic Information Systems software (e.g., ArcGIS, QGIS) is required
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design. The primary focus of the lab is on G protein-coupled receptors (GPCRs), particularly those involved in cardiovascular and hormone signaling pathways. Using multiscale simulations—combining
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Postdoctoral researcher (f_m_x) - Waves in the Inner-magnetosphere and their Effects on Radiation...
numerical simulations to study the effect of various plasma waves on the dynamic evolution of radiation belt electrons. Your responsibilities: The successful candidate will have extensive experience in
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nanocrystals and carry out Brownian and molecular dynamics simulations of their self-assembly behavior in solution, on surfaces, or trapped at fluidfluid interfaces. 2) Carry out free energy calculations using
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dynamics simulations to investigate photoinduced processes and connect them to timescales obtained from nonlinear electronic spectroscopic measurements Plan and conduct simulations and work with
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, molecular dynamics simulations using ab initio and machine-learning potentials, and the development or application of machine-learning tools for feature extraction, property prediction, and inverse molecular