70 parallel-computing-numerical-methods Postdoctoral research jobs at University of Minnesota
Sort by
Refine Your Search
-
computing (HPC) and parallel processing to enable the analysis of massive datasets. Experience in advanced statistical inference (e.g., Bayesian statistics, spectral methods) for extracting robust patterns
-
not eligible for H-1B visa sponsorship. Duties/responsibilities: -performing high level experimental, theoretical, and numerical research and data analysis (55%) -presentation publication, and proposal
-
, viscoelastic, and damage-informed formulations) under complex thermo-mechanical loading. Implementing and validating models using computational tools (e.g., numerical solvers, finite element frameworks
-
experiments using methods created according to previously published methods or novel methods developed as needed • Analyze data collected from experiments, generate manuscript figures, write and edit
-
research group focuses on mixed-methods studies on attitudes related to SOGI and bias-based bullying in schools. The position is 30% teaching (FsoS 1201: Human Development) and 70% research. The successful
-
with an expertise in dynamical systems, stochastic processes or network dynamics in the context of mathematical biology. Prior experience with mathematical/computational neuroscience and scientific
-
guidelines. For more information, see https://policy.umn.edu/hr/postdocappoint Responsibility • Lead innovative research on VLM/VLA methods and their applications in autonomous driving and ITS problem
-
for presentation. Instruct students, fellows and other inexperienced professional persons in proper laboratory methods and procedures. Qualifications Required Qualifications: A Doctorate Degree (PhD, which is
-
motivated individual with a background in decision analysis and simulation modeling methods who is interested in applying these tools to answer policy-relevant questions about eMTCT interventions. Our group
-
scientists and scholars in those areas. Successful candidates will demonstrate how their mathematical and computational work makes substantive contributions to advancing these fields. Applications are welcome