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.


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
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

Temporary Research Assistant Positions at the U-M Center for the Assessment of Tobacco Regulations (CAsToR)

By | General Interest, SC2 jobs

Center for the Assessment of Tobacco Regulations LogoThe Center for the Assessment of Tobacco Regulations (CAsToR) aims to provide evidence-based and expert-informed modeling of the behavioral and public health impacts of tobacco regulations. Funded through the TCORS 2.0 program, this multi-institutional Center includes experts in the field of tobacco regulatory science and modeling from the University of Michigan, Georgetown University, Yale University, University California San Francisco, and University of Minnesota.

CAsToR is looking to hire up to two temporary research assistants in the University of Michigan School of Public Health Epidemiology Department, one who will primarily work on a nicotine reduction agent-based model and another who will support a pilot project using machine learning techniques to look at smoking status transitions. The ideal candidates are current graduate students (masters or doctoral level).

  • Temporary Part Time Position (Research Assistant II)
  • Hours: Up to 20 hours per week, remote preferred
  • Pay Rate: $15-28 dependent upon experience

Apply Now

Los Alamos Computational Physics Student Summer Workshop

By | General Interest, Happenings

Los Alamos Computational Physics Student Summer Workshop

The Los Alamos Computational Physics Student Summer Workshop seeks to bring a diverse group of exceptional undergraduate and graduate students for informative, enriching lectures and to work with its staff for 10 weeks on interesting, relevant projects that may culminate in articles or conference presentations. Students are organized into teams of 2 working under the guidance of one or more mentors.


  • Why explosions look like earthquakes
  • Numerical investigation of explosive particle jetting
  • Materials phase diagrams from density functional theory
  • Uncertainty quantification in high-explosive equations of state
  • Photon transport in warm dense matter
  • Equations of state for modeling high-explosives
  • Deep neural networks for a photon and neutron transport problem
  • Emulating fission observables
  • Code verification for MCNP unstructured mesh geometry
  • Two mesh radiation-hydrodynamics methods
  • Using Richtmeyer-Meshkov instability to study the constitutive behavior of solid media subjected to shock-loading
  • They dynamics of plasma jets moving in the hot medium

Applications are now open for this year’s workshop, which will run from Monday, June 8, until Friday, August 14, 2020. Applications are due by January 20, 2020.

For previous year’s research reports, information about stipends, how to sign-up for the mailing list, and complete application instructions, visit

Applications are accepted from US citizens only.

2020 SIAM Mini-Symposium in Applied Mathematics

By | Events, General Interest, Happenings

2020 SIAM Mini-Symposium in Applied Mathematics

The SIAM student chapter at the University of Michigan is hosting a student mini-symposium in applied mathematics on May 29, 2020. This event will allow students from different disciplines in the area to see what is being done in the field and promote interest in applied mathematics in general. This mini-symposium is open to all graduate students at the University of Michigan whose research is related to applied mathematics and/or scientific computing.

Time: Friday, May 29th, 10:00am – 4:00pm

Location: East Hall 3096, Department of Mathematics

Important Deadlines:

Deadline for submission of abstracts: April 14, 2020

Registration deadline: May 5, 2020

Registration is Open!

Registration to attend the 2020 SIAM Student Mini-Symposium in Applied Mathematics is now open. All are welcome to attend the conference, regardless of registration status, but lunch will be provided only for registered attendees.

To register please fill out the form provided by May 5, 2020.


The link for the mini-symposium can be found here:

MICDE funds 7 new catalyst projects

By | General Interest, Happenings, News

Every year, The Michigan Institute for Computational Discovery & Engineering (MICDE) Catalyst Grants fund innovative research projects in computational science that combine elements of mathematics, computer science, and cyberinfrastructure.

Topics of interest include, but are not limited to:

  • Computational science approaches, algorithms, frameworks, etc.
  • Emerging paradigms in computing (exascale computing, quantum computing, FPGA computing, etc.)
  • Applications in emerging areas (neuroscience, ecology, evolutionary biology, human-made complex systems, mobility etc.)
  • Extensions of traditional computational sciences to complex decision making (reinforcement learning, transfer learning, neuromorphic computing, etc.)
  • Artificial Intelligence informing and informed by science

This year, MICDE awarded its third round of catalyst grants to faculty leading seven innovative projects in computational science.

The projects, supported by up to $90,000 in grant funding, span several research areas ranging from cosmology to artificial intelligence systems in computational systems.

Learn more about the 2019-2020 catalyst grants.

The background image is a multi-color image of the Milky Way disk, its halo and nearby satellite galaxies obtained with the European Space Agency’s Gaia Satellite ( . The blue curve shows an example of (half) of a regular trajectory that a star in the halo of the Milky Way might follow. [M. Valluri, Astronomy]

MICDE announces 2019-2020 fellowship recipients

By | Educational, General Interest, Happenings, News

The Michigan Institute for Computational Discovery and Engineering (MICDE) is pleased to announce the 2019-2020 MICDE Fellowship recipients. They were chosen to receive this honor because of their exceptional academic record and the outstanding promise of their research in computational sciences. Fellows are working on a wide range of groundbreaking problems, including the strategic interaction of parties and electors in democratic elections (S. Baltz, Political Science), the effects of disruption of synaptic signaling on neuronal structures (M. Budak, Biophysics),  and on the development of robust, efficient, and scalable algorithms for multidisciplinary design optimization applications applied to the design of the next generation of fuel-efficient aircrafts (A. Yildirim, Aerospace). The fellowships, which carry a $4,000 stipend, are meant to augment other sources of funding and are available to students in our three educational programs. Visit our fellowship page to learn more about the program and the fellows.

2019-2020 MICDE Fellows (from left to right) Guodong Chen (Aero), Suyash Tandon (ME), Jiale Tan (Epidemiology), Fuming Chang (ClaSp), Kelly Broen (Epidemiology), Bradley Dice (Physics), Liz Livingston (ME), Will Weaver (EEB), Yuan Yao (ME), Samuel Baltz (Pol Sci), Joe Hollowed (Physics), Minki Kim (ME), Allison Roessler (Chem), Chongxing Fan(ClaSp), Maral Budak (Biophysics), Saibal De (Math), Xian Yu (IOE), Jiaming Zhang (Physics). [Not pictured: Thomas Waltmann (Physics), Anil Yildirim (Aero), and Jessica Conrad (IAM)]


Samuel Baltz, Political Science
Kelly Broen, Epidemiology
Maral Budak, Biophysics
Fuming Chang, Climate and Space Sciences and Engineering
Guodong Chen, Aerospace Engineering
Jessica Conrad, Applied & Interdisciplinary Mathematics
Saibal De, Applied & Interdisciplinary Mathematics
Bradley Dice, Physics
Chongxing Fan, Climate and Space Sciences and Engineering
Joseph Hollowed, Physics
Minki Kim, Mechanical Engineering
Elizabeth Livingston, Mechanical Engineering
Allison Roessler, Chemistry
Jiale Tan, Epidemiology
Suyash Tandon, Mechanical Engineering
Thomas Waltmann, Physics
William Weaver, Ecology and Evolutionary Biology
Yuan Yao, Mechanical Engineering
Anil Yildirim, Aerospace Engineering
Xian Yu, Industrial & Operations Engineering
Jiaming Zhang, Physics

Ruiwei Jiang wins NSF CAREER award for work in operations research

By | General Interest, Happenings, News

Ruiwei Jiang, assistant professor in Industrial and Operations Engineering and an MICDE-affiliated faculty member, has won an NSF CAREER award for work evaluating the potential benefits of incorporating decision-dependent uncertainty into decision-making problems in service industries and investigate new optimization approaches to maneuvering such uncertainty to improve decision-making.

Read more…

Women in HPC launches mentoring program

By | Educational, General Interest, HPC, News

Women in High Performance Computing (WHPC) has launched a year-round mentoring program, providing a framework for women to provide or receive mentorship in high performance computing. Read more about the program at

WHPC was created with the vision to encourage women to participate in the HPC community by providing fellowship, education, and support to women and the organizations that employ them. Through collaboration and networking, WHPC strives to bring together women in HPC and technical computing while encouraging women to engage in outreach activities and improve the visibility of inspirational role models.

The University of Michigan has been recognized as one of the first Chapters in the new Women in High Performance Computing (WHPC) Pilot Program. Read more about U-M’s chapter at

Balzano wins NSF CAREER award for research on machine learning and big data involving physical, biological and social phenomena

By | General Interest, Happenings, News, Research

Prof. Laura Balzano received an NSF CAREER award to support research that aims to improve the use of machine learning in big data problems involving elaborate physical, biological, and social phenomena. The project, called “Robust, Interpretable, and Efficient Unsupervised Learning with K-set Clustering,” is expected to have broad applicability in data science.

Modern machine learning techniques aim to design models and algorithms that allow computers to learn efficiently from vast amounts of previously unexplored data, says Balzano. Typically the data is broken down in one of two ways. Dimensionality-reduction uses an algorithm to break down high-dimensional data into low-dimensional structure that is most relevant to the problem being solved. Clustering, on the other hand, attempts to group pieces of data into meaningful clusters of information.

However, explains Balzano, “as increasingly higher-dimensional data are collected about progressively more elaborate physical, biological, and social phenomena, algorithms that aim at both dimensionality reduction and clustering are often highly applicable, yet hard to find.”

Balzano plans to develop techniques that combine the two key approaches used in machine learning to decipher data, while being applicable to data that is considered “messy.” Messy data is data that has missing elements, may be somewhat corrupted, or is filled heterogeneous information – in other words, it describes most data sets in today’s world.

Balzano is an affiliated faculty member of both the Michigan Institute for Data Science (MIDAS) and the Michigan Institute for Computational Discovery and Engineering (MICDE). She is part of a MIDAS-supported research team working on single-cell genomic data analysis.

Read more about the NSF CAREER award…