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the Postdoctoral Appointee's research. Collegial conduct towards members of the research group and others as described in the Duke University School of Medicine Honor Code of Professional Conduct and other relevant
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for grid resilience assessments, such as NERC CIP standards, as well as equity frameworks and methodologies. Experience working collaboratively in version control systems for source code management such as
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such as GitHub Workflow, servers, and AI coding tools is essential, as is a strong background in either PyTorchor JAX. Applicants must have completed their Ph.D. prior to the beginning of their appointment
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experience with numerical modeling codes such as ASPECT or Underworld Geodynamics (UWG). Preferred Qualifications: Familiarity with landscape evolution modeling tools like Fastscape or BADLANDS is highly
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, multiscale modeling, molecular simulation code/software (e.g., LAMMPS, GROMACS), machine learning. Prior experience with applying simulations to biomolecular systems is a plus but not required. Applicants
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Previous Job Job Title Post-Doctoral Associate Next Job Apply for Job Job ID 368778 Location Twin Cities Job Family Academic Full/Part Time Full-Time Regular/Temporary Regular Job Code 9546 Employee
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coding experience with e.g. Python/Matlab/R Practical experience with High Performance Computing, and scientific programming and a willingness to learn to work with high-performing computing systems
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funded by the National Science Foundation. The position is focused on performance analysis and optimization of the MILC code and the libraries it calls such as QUDA or Grid. The successful applicant can
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experience with numerical modeling codes such as ASPECT or Underworld Geodynamics (UWG). Preferred Qualifications: Familiarity with landscape evolution modeling tools like Fastscape or BADLANDS is highly
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of the new methods. Draft articles describing new AI based methods for publication in peer reviewed journals. Programming: 30% Create a well-documented code to form the basis for future operational models