Faculty Positions in Mechanical Engineering at the Ecole Polytechnique Fédérale de Lausanne (EPFL)

By | News, SC2 jobs

The Institute of Mechanical Engineering at EPFL invites applications for two faculty positions at the level of tenure track Assistant Professors in the fields of Sustainable Manufacturing and Biomechanics.

For the position in Sustainable Manufacturing, we seek applicants who will broadly address the engineering challenges related to developing intelligent manufacturing systems, while attending to the multiple facets of sustainability. Research areas of interest include, but are not limited to: (i) intelligent advanced manufacturing systems; (ii) data-driven manufacturing; and (iii) additive manufacturing. Given that high value-added manufacturing is an essential pillar of the Swiss economy, applicants are expected to demonstrate a potential for direct interactions

with industrial partners.

For the position in Biomechanics, we seek applicants with a mechanics background who will address research challenges related to the development of theoretical and computational models to investigate, and potentially control or design, biological materials and systems. Research areas of interest include, but are not limited to: (i) cell and tissue mechanics; (ii) architected biomaterials; (iii) prosthetic and assistive mechanical devices; and (iv) pre-operative modeling for surgical interventions.

As a faculty member of the School of Engineering, the successful candidate is expected to initiate an independent and creative research program, and commit to excellence in both undergraduate and graduate teaching. EPFL offers internationally competitive salaries, generous research support, significant start-up resources, and outstanding research infrastructure.

How to apply

Applications should include a cover letter with a statement of motivation, curriculum vitae, list of publications and patents, research plan and teaching interests. Applicants should provide the names and addresses of at least 3 referees who are ready to supply a reference letter upon request.

Applications must be uploaded in PDF format to the recruitment web site.

Formal evaluation of candidates will begin on December 1st, 2022.

Enquires may be addressed to:
Prof. Herbert Shea
Search Committee Chair
e-mail: igm-search@epfl.ch

For additional information on EPFL, please consult the websites: www.epfl.ch, sti.epfl.ch,

EPFL is an equal opportunity employer and family friendly university. It is committed to increasing the diversity of its faculty. It strongly encourages women to apply.

Logo EPFL, École polytechnique fédérale de Lausanne

Tutorial Workshop – Isaac Newton Institute

By | Educational, Events, News

Workshop theme

This week-long workshop will provide an introduction to the core theoretical and applied engineering topics of the DDE programe. Three sessions will be devoted to foundational techniques and methodologies including (i) reinforcement learning and control, (ii) uncertainty quantification and data assimilation, and (iii) model reduction. Another three sessions will be devoted to introductions to current and future challenges for data-driven engineering arising from (i) aeronautics, (ii) chemical and (iii) structural engineering. The tutorials will lay the foundation for the follow-up activities of the DDE programe and the deep-dive study periods in particular. The tutorial workshop is suited in particular for PhD students, postdocs and earlier career scientists from mathematics, statistics, computer science, and computational engineering.


  • Sean Meyn (Algorithm design for reinforcement learning and optimization)
  • Sebastian Reich (Uncertainty quantification and data assimilation)
  • Karthik Duraisamy (Model order reduction for complex systems)
  • Luca Magri (Physics aware machine learning in engineering),
  • Antonio del Rio Chanona (Process control and supply chain optimization)
  • Elizabeth Cross (Data-driven structural assessment)


January 16 – 20, 2023


Cambridge, UK or Online (more information in the application section)

More information

Application Deadline: 30 Sep 2022


By | Educational, SC2 jobs

Prof. Jesse Capecelatro in the Department of Mechanical Engineering is currently seeking a GSRA for a DOE-sponsored project related to methane ares.

Job Description

The project will involve performing CFD simulations of methane ames in the presence of turbulent cross-winds and using machine learning to guide improved burner designs. The student must be admitted in College of Engineering or Applied Math and have experience using OpenFOAM (or related CFD) and course work in turbulence and combustion.


How to Apply

If you are interested in this position or want to learn more, please email your curriculum vitae to Jesse Capecelatro at jcaps@umich.edu with subject line REM-EDY.


By | Educational, Funding Opportunities, SC2 jobs

Dr. Harish Ganesh (Department of Naval Architecture and Marine Engineering), Prof. Jesse Capecelatro (Department of Mechanical Engineering), and Prof. Steven Ceccio (Department of Mechanical Engineering) are currently seeking a post-doctoral scholar for a one-year position.

Job Description:

This position involves developing numerical methods to leverage time-resolved 3-D experimental measurements using Particle Image Velocimetry (PIV) and Particle Tracking Velocimetry (PTV). Specifically, the project aims at developing a particle based numerical framework to augment experimentally obtained PTV data in the near- and far-wake behind a bluff body. The candidate should have a PhD in Engineering or a related field (e.g., Physics, Mathematics, or Computer Science) with experience in Scientific Computing (proficiency in MPI and Python) and an interest in high Reynold’s number turbulent flows.

How to Apply:

If you are interested in this position, please email your curriculum vitae and at least two references to Jesse Capecelatro at jcaps@umich.edu.

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.


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.