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.

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.

MICDE’s InfoReady portal logging in issue

By | Uncategorized

We are working on resolving a bug when logging in into the MICDE InfoReady portal using U-M’s SSO. While we fix it, if you are getting the following screen:

please follow these steps:

  • Go to https://micde.infoready4.com/#login.
  • Scroll down to the Login for Other Users, and click Forgot your password.
  • Enter your umich email address and then click Reset Password. An email will be sent to that address with instructions for resetting your password.
  • Follow the instructions, and you will be redirected to the site and logged in automatically.

You can use the Login for Other Users instead of the Single Sign On as long as necessary; the password will not change unless you change it in your User Profile.

We apologize for any inconvenience.

Professor Karthik Duraisamy named new director of the Ph.D. in Scientific Computing program

By | Educational, Feature
Prof. Karthik Duraisamy infront of screen with turbulence simulation

Professor Karthik Duraisamy (Aerospace Engineering)

Karthik Duraisamy, associate professor of Aerospace Engineering, and an associate director of the Michigan Institute for Computational Discovery & Engineering, has been named director of the joint Ph.D. in Scientific Computing program effective on January 1, 2022. Professor Duraisamy’s research involves the development of theory and algorithms for computational modeling of complex physical systems. He was the principal investigador of ConFlux, an NSF Major Research Instrumentation project that led to the development of a first of its kind computing instrument specifically designed to enable High Performance Computing (HPC) clusters to communicate seamlessly and at interactive speeds with data-intensive operations. Currently he directs the Air Force Center of Excellence on Rocket Combustion modeling. He is invested in educating future researchers with a strong computational background capable of using the power of computing for problem solving. He worked with the group that launched the course Methods and Practice in Scientific Computing, and developed and teaches a course on data-driven analysis and modeling of complex systems. These two courses give students a solid foundation, enabling them to use HPC in their research. 

Portrait of Ken Powell

Professor Ken Powell (Aerospace Engineering)

Professor Duraisamy replaces Ken Powell, Arthur F. Thurnau Professor of Aerospace Engineering, who stepped down from the role after 18 years of service. As a young assistant professor, Professor Powell was an instrumental member of the original team that conceived and launched the program back in 1989. The field of computational fluid dynamics, where his research interests lie, has always included an active community of HPC users and developers, thus he was always actively involved in the program through research, teaching and student advising. In 2004 he succeeded Professor William Martin as director of the program. During his time as director, he met and advised every single one of the over 350 students that enrolled in the program. Through this time he became an expert on scientific computing courses across the university, and witnessed first hand the explosion in computational and data science usage, reflected in the research scope of the students enrolling in the program.

Professor Duraisamy has big shoes to fill, but he is being assisted by the MICDE Management and Education Committee. The program’s mission, to train U-M students in scientific computing and to support the growing computational and data science community at the University of Michigan, will itself continue to expand.

The University of Michigan Ph.D. in Scientific Computing timeline. Read more.

 

XSEDE HPC Workshop: BIG DATA and Machine Learning

By | Educational, Events, HPC

XSEDE and the Pittsburgh Supercomputing Center are offering a two day Big Data and Machine Learning virtual workshop that will focus on topics including big data analytics and machine learning with Spark, and deep learning using Tensorflow.

When: Wed., April 6 @ 11:00 a.m. – 5:00 p.m. E.S.T. & Fri., April 8 @11:00 a.m. – 5:30 p.m. E.S.T.

Registration closes on April 4, 2022. Space is limited.

Tentative Agenda

Wednesday, April 6
All times given are Eastern
11:00 Welcome
11:25 A Brief History of  Big Data
12:20 Intro to Spark
1:00    Lunch break
2:00    More Spark and Exercises
3:00    Intro to Machine Learning
5:00    Adjourn

Friday, April 8
All times given are Eastern
11:00 Machine Learning: Recommender System with Spark
1:00    Lunch break
2:00    Deep Learning with Tensorflow
5:00    Tying it All Together
5:30    Adjourn

Job Opening: Physics-AI Hybrid Modeling Research Engineer at Bosch

By | Feature, SC2 jobs

The Bosch Research and Technology Center in Sunnyvale, CA seeks to hire an outstanding research engineer to develop novel hybrid multiscale, cross-domain modeling and simulation tools for Bosch products. This engineer would join a team of PhDs with a variety of competences including high fidelity CFD-based multiphysics modeling, adjoint-based optimization, machine learning and high performance computing. The team focuses on design and optimization of novel clean and sustainable energy solutions such as fuel cells and electric vehicle components.

Primary responsibilities:

  • Build models which utilize machine learning and hybrid modeling approaches to capture complex physical phenomena and accelerate solution time of physical models
  • Develop multiscale models together with materials and systems modelers
  • Develop hybrid performance and aging models for Bosch products including polymer electrolyte fuel cells
  • Integrate hybrid performance and aging models into system simulation
  • Collaborate with experimentalists, top universities and our partners in Silicon Valley

Read more.

 

Applications to the 2022 Annual Argonne Training Program on Extreme-Scale Computing are due March 1

By | Educational, HPC

Argonne Training Program on Extreme-Scale ComputingThe annual Argonne Training Program on Extreme-Scale Computing (ATPESC), for doctoral students, postdocs, and computational scientists, is set to take place July 31-August 12, 2022. This year’s program will mark the 10th anniversary of ATPESC.

Submit your application for an opportunity to learn the tools and techniques needed to carry out computational science on the world’s most powerful supercomputers. ATPESC participants will have access to DOE’s leadership-class systems at the ALCF, OLCF, and NERSC.

Call for 2022 Applications extended to March 7

Learn more and apply here

PROGRAM CURRICULUM
Renowned scientists and leading HPC experts will serve as lecturers and guide the hands-on sessions. The core curriculum will cover:

  • Hardware architectures
  • Programming models and languages
  • Approaches for performance portability
  • Numerical algorithms and mathematical software
  • Performance measurement and debugging tools
  • Data analysis, visualization, and methodologies for big data applications
  • Approaches to building community codes for HPC systems
  • Machine learning and data science

ELIGIBILITY AND APPLICATION
Doctoral students, postdocs, and computational scientists interested in attending ATPESC can review eligibility and application details on the website.

There are no fees to participate in ATPESC. Domestic airfare, meals, and lodging are also provided.
Application deadline: March 1, 2022.

ATPESC is funded by the Exascale Computing Project, a collaborative effort of the DOE Office of Science’s Advanced Scientific Computing Research Program and the National Nuclear Security Administration.

Postdoc Position: Computational Modeling in Immunology of Tuberculosis

By | Feature, SC2 jobs

HIRING IMMEDIATELY.

About the Position:

An exciting opportunity is available for a strong mathematical/computational modeler to work in a multidisciplinary team on immune responses in the context of tuberculosis.  The position is available jointly in the laboratories of Jennifer Linderman in Chemical Engineering and Denise Kirschner in the Department of Microbiology and Immunology, both at the University of Michigan. The project uses a systems biology approach to integrate our multi-scale and multi-organ in silico models with data from humans and non-human primates derived by our collaborators. An estimated one-third of the human population is infected with the pathogen Mycobacterium tuberculosis, mostly in rural areas within developing countries, making it a critical global health issue.

Qualifications:

  • Ph.D. degree (or equivalent) in engineering or mathematics or a closely related field
  • Strong computational skills and experience in mathematical modeling in biology
  • The ideal applicant will have extensive experience in object-oriented programming and/or use of MATLAB, R
  • Experience with python is a plus
  • Desire and ability to read scientific literature in immune response to tuberculosis
  • Good communication skills and the ability to work in an interdisciplinary team are essential

How to apply:

Send a CV, names of 3 references, and a letter describing research interests and summarizing Ph.D. work to both Jennifer Linderman linderma@umich.edu and Denise Kirschner kirschne@umich.edu. Copies of papers authored by the applicant are welcome.  Those under-represented in STEM are especially encouraged to apply.

Reminder: seeking nominations for MICDE graduate fellowships 2022-2023 

By | Educational, Funding Opportunities
MICDE is currently accepting nominations of prospective students for an MICDE graduate fellowship. If you are an U-M faculty, and have identified an incoming graduate student interested in research in Computational Discovery and Engineering with your research group, we invite you to nominate them for the award. MICDE seeks to recruit and retain a diverse cohort of students to contribute to building a more diversified, equitable and inclusive STEM community. Please keep this is mind when sending your nomination. Nominations will be reviewed on a rolling basis. We will accept nominations until we reach our funding capacity, but no later than Friday, March 11, 2022.

Postdoctoral Researcher or Assistant Research Scientist in Navy Acoustics and/or Hydrodynamics

By | General Interest, SC2 jobs

The Department of Naval Architecture and Marine Engineering at the University of Michigan is looking for a US-citizen postdoc or research scientist with skill(s) in structural acoustics & vibrations, underwater acoustics, or hydroacoustics, but will also consider anyone at or above the post-doctoral level who has a willingness to learn about these topics.

Location: Ann Arbor, Michigan
Duration: 1–3 years
Start date: Immediate

Job Description

A post-doctoral-level or higher scientist or engineer is sought for basic research studies into
acoustics and hydrodynamics of enduring interest to the US Navy. The successful applicant will
have or be willing to develop a mixture of experimental, computational, and analytical skills; a
desire to work with and assist undergraduate and graduate students; and a sincere interest in
performing research that leads to publications in top journals. Preferred applicants will have
expertise in one or more of the following areas (and a willingness to learn about the others):
array signal processing, acoustic wave propagation, structural wave propagation, wall-bounded
turbulence, and machine learning. The position is supported by US Government grants and
contracts, and University of Michigan resources.

Requirements

US citizenship is required. Eligible applicants will have completed their Ph.D. in physics, math,
acoustics, engineering, or another relevant field. Underwater acoustics or signal processing
experience is preferred, but all candidates are encouraged to reach out.

Application Materials

Cover Letter
CV/Resume
Short statement of research skills & interests
Names and contact information for up to three references

Please send application materials or questions about the position to Prof. David R. Dowling at
drd@umich.edu.