14 parallel-computing-"Virginia-Tech" Fellowship positions at Michigan State University
Sort by
Refine Your Search
-
environments, and high-performance or parallel computing is desirable. The candidate will also prepare technical documentation, reports, peer-reviewed publications, and presentations and collaborate
-
, dynamic-link libraries, SQL, Git or other version-control systems, Linux, high-performance computing, parallel computing, or automated testing Experience with watershed processes, groundwater-surface
-
analysis, scientific computing, PDE together with research experience in scientific machine learning, are particularly encouraged to apply. Required Application Materials Applications will be reviewed
-
, agentic multi-modal data science for complex transport phenomena, in addition to forward/backward uncertainty quantification, numerical analysis, and high-performance computing. Equal Employment
-
parallel projects will ensure the development of independent projects to support the long-term career goals of the applicant. Generally, the project will center around leveraging bacterial and mammalian
-
, biodiversity), U.S. agricultural and conservation policy, and / or Process-based ecosystem models and their outcomes Knowledge of statistical analysis, and experience using one or more statistical computing
-
systems, including embedded and resource constrained systems with various heterogenous computing topologies Additional responsibilities include Assisting with development of GUI software tools to
-
independently Confidence with computational biology including use of programming languages such as R, python and some familiarity with high performance computing Excellent communication and interpersonal
-
conducting and analyzing molecular dynamics simulations Experience using high-performance computing platforms Experience developing neural network models Experience using AI-assisted coding tools for
-
policy, agronomy, or a related field Desired Qualifications Strong skills in satellite remote sensing, GIS, and statistical analysis. Experience using cloud-based computing resources (e.g. Google