News

Jun 10
0

NVIDIA Academic Hardware Grant Program

By | Funding Opportunities, Research

The NVIDIA Academic Hardware Grant Program endeavors to advance education and research by:

  1. Enabling groundbreaking, innovative, and unique academic research projects with world-class computing resources.
  2. Providing educators with a hands-on platform to teach AI, deep learning, and data science to students in any discipline.

Eligibility

Must be a member of the NVIDIA Developer Program to qualify

  • For Researchers:
    • Applicant must be a faculty or PhD student researcher at a university or research institute
    • Application must demonstrate clear understanding of how to use NVIDIA technology to accelerate research and significantly impact the success of the project
  • For Teachers and Instructors:
    • Applicant must be a teacher or administrator at a college, university, primary/secondary school, or non-profit STEM organization
    • Course must make use of NVIDIA SDKs and give students a hands-on opportunity to hone skills

This is a competitive program. Not all projects that meet the eligibility requirements will be awarded.

Application Window – Key Dates:

  • Opens: June 20, 2022 9:00 AM PT
  • Closes: July 1, 2022 6:00 PM PT
  • Award Decisions Sent By: August 26th, 2022

You can find the application form and more information about the grant on NVIDIA`s website.

Jun 07
0

Postdoc Position at Johns Hopkins University

By | Educational, Funding Opportunities, SC2 jobs

Profs. Michael Shields and Lori Graham-Brady are seeking a postdoctoral scholar for a joint collaborative program on uncertainty quantification of mechanical property predictions based on data-driven and/or machine learning models. In the short term, the focus of this project will be on developing UQ tools for Deep Neural Network models that connect image data to material properties. In the longer term this is expected to expand to a spectrum of ML and other data-driven models. Finally, we hope to explore UQ for interconnected models, e.g., in a hierarchical multi-scale construct.

Successful candidates for the position will have a demonstrated track record of scholarly research, and experience in uncertainty quantification, machine learning, and/or computational mechanics. Due to the broad range of expertise requested, we are open to candidates who have more significant expertise in one of these areas and who are interested in developing further knowledge in the other domains. Initial appointment is for one year with the expectation of renewal for a second year pending satisfactory performance. We are committed to recruiting a diverse community of faculty, students, and staff, and to cultivating an inclusive environment that supports, fosters and celebrates all the ways in which the broad differences among us make us better.

Interested candidates are asked to submit their CV and a brief cover letter to Profs. Graham-Brady and Shields. Please email materials to both lori@jhu.edu and michael.shields@jhu.edu.