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On-Site Lead Staff Scientist

By | SC2 jobs

ERDC DSRC On-site Lead Staff Scientist

The Engineer Research and Development Center (ERDC) in Vicksburg, MS is looking for candidates for the Site Lead position. The position description is below and a Secret clearance is required.

Responsibilities

  • Works with HPCMP customers to identify potential multidisciplinary efforts.
  • Participates on appropriate teams as part of the multidisciplinary efforts.
  • Facilitates the process by which efforts are presented for consideration to the Government.
  • Supports major efforts and may serve as principal investigator.

Primary interface with Government leadership.

Role/Qualifications

  • PhD required.
  • 10 years of HPC-related experience preferred. (flexible for strong candidates)
  • Demonstrated experience in multidisciplinary computational environments.

Documented authorship in peer-reviewed publications.

 

They are also looking for scientists with DDA experience, and they could be located at ARL (Aberdeen, MD), AFRL (Dayton, OH), Navy (Stennis, MS) or ERDC (Vicksburg, MS). Description of what they are specifically defining DDA as is below.

Data and Decision Analytics (DDA)

DDA covers the entire computational ecosystem (hardware, software, storage, and networks) required to conduct large-scale data analytics.  This ecosystem includes how large data is managed, analyzed, and visualized. Capabilities include methods for conducting exploration (what does the data look like?), descriptive (what happened?), diagnostics (why did it happen?), predictive (what will happen?), and prescriptive (how can we make it happen?) analyses.  In this computational area, the Contractor shall:

  • Work with the HPCMP user base to identify requirements for software and hardware in the area of DDA
  • Provide software engineering support for development and improvement of DDA codes
  • Provide expert support for the R programming language and R studio
  • Provide application-level support for DDA tools including but not limited to Caffe, Tensorflow, Sparc, python, anaconda H2O, and container technologies
  • Provide technical support to DDA users/customers across DoD
  • Foster and develop collaborations with DoD and non-HPCMP user and customers.
  • Identify opportunities, requirements and promising research approaches to exploit and leverage promising data science capabilities. Potential areas include:
    • Cognitive modeling
    • Automated Target Recognition (ATR) (e.g., DARPA Trace program)
    • Test range and training center data streams
    • Autonomy – Supervised and unsupervised machine learning methods
    • High-throughput screening
    • Automated fitting and multiscale approaches
    • Intrusion-resilient cyber systems and cyber vulnerability assessments and reactions
    • Decision-support systems and augmentation of human performance
    • Utilization of relational databases, non-relational databases, polystores, and other data management methodologies
  • Implement algorithmic cores and new work-stream tools and collaborate with PET on-sites to promote the adoption of HPDA within the HPCMP community.
  • Provide leadership to identify, explore and evaluate data science software tools for inclusion within the HPCMP software stack and user community.
  • Collaborate with the HPCMP and Centers team to determine when traditional HPC hardware and middleware is appropriate for HPDA problems and tools.  Alternatively, provide guidance if and when specialized hardware, middleware, or system configurations would be more optimal.
  • Provide technical support to SIP customers/users for existing and emerging software in terms of usability, performance optimization, validation/verification and strong/weak scaling.
  • Foster and develop collaborative relationships with DoD and non-DoD communities.

Research Data Scientist Intermediate for ARC-TS

By | SC2 jobs

Advanced Research Computing – Technology Services (ARC-TS) has an exciting opportunity for those who wish to impact our world through science and research by use of computational and data tools such as, Machine Learning, statistical analysis, High Performance Computing (HPC), Big Data (Hadoop, Spark, DBMS, etc), cloud computing services (AWS, Azure, GCP), and more.

This position will be part of a team supporting all areas of research that utilize data at the University of Michigan.  The primary responsibilities will be consulting on as well as providing services in collecting, discovering, cataloging, manipulating, and transforming data.  This role will work closely with possibly multiple projects. Other responsibilities will include making presentations and providing training on the use, cataloging, and manipulation of data to students and researchers.

The successful candidate should be comfortable with Linux systems and the use of common data manipulation tools and languages such as Python and SQL and be able to pick up new tools quickly as needed for the scope of the project currently assigned.

Note: Technical training will be provided to address specific gaps in desired qualifications.

Responsibilities

Data Preparation and Identification — This role will help users through the lifecycle of their datasets.  The position will help users understand the data set that they have, determine programmatic ways to clean the data, prepare the data for analysis and annotate datasets with descriptions for multiple uses.  We also foresee the role helping to identify existing datasets around the University that could be used by courses and for research.  Data Collection and Programing — Your role will assist in the creation of tools that collect data from many disparate sources such as SQL and NoSQL, databases,  APIs, web scraping, flat files, and other file formats. Your interaction with the research projects may include extended functionality to manipulate, identify duplicates, removing identifying data, etc through the use of tools. Documentation and Training of Tools — Your role will participate in a larger group to provide workshops on the use of data and data manipulation tools.  This will include creating documentation of how to use tools in our supported environments such. Documentation and Cataloging of Data — Your role will document data such as meta-data, schemas and more so that researchers may consume prepared data for use in their own analysis.  This documentation will include how the data are manipulated and assumptions used for any summaries or statistics. Development of Self and Others — You will explore new tools and technologies through formal and self-directed learning. Research and provide advice to team on latest application technology trends to support ongoing development of existing tools and services.

Required Qualifications

  • Bachelors degree in a related field and/or equivalent combination of education, certification and experience
  • Two (2) years of experience in collecting, discovering, cataloging, manipulating, and transforming data
  • Python Proficiency
  • Very Basic SQL experience
  • Linux Proficiency
  • Experience with data from different fields and domains
  • Comfortable supporting a broad range of research (students, researchers, and faculty)
  • Ability to communicate effectively via email, letters, and in person to teams and customers
  • Ability to work independently and collaboratively

Desired Qualifications

  • Masters or PhD in related area
  • Experience working in an academic environment
  • Familiarity with big data tools from the Hadoop ecosystem such as Mapreduce, Spark, Hive, Impala, etc.
  • Understanding of any of the following numerical techniques:  causal inference, selection bias, dimensionality reduction (Singular value decomposition, Principal component analysis)
  • Understanding of Machine Learning tools such as Tensorflow, PyTORCH, Scikit, CNTK/Microsoft Cognitive Toolkit, Power AI, Theano, Caffe, etc.
  • Understanding of Machine Learning/AI methods such as random forest, neural networks, Markov models, etc.
  • Proficiency in any of the following:  R, SAS, SPSS, Tableau, Perl, C/C++, Go, etc.
  • Advanced SQL experience
  • Experience with any of the following:  Compilers, Makefiles, and common build chains (autoconf/automake, CMake, pip, easy_build, Spack)

Diversity, Equity and Inclusion

The University of Michigan Information and Technology Services seeks to recruit and retain a diverse workforce as a reflection of our commitment to serve the diverse people of Michigan, to maintain the excellence of the University and to offer our students richly varied disciplines, perspectives and ways of knowing and learning.

Comprehensive Benefits

The University of Michigan Benefits Office is committed to offering a high-quality benefits package to support faculty, staff and their families.  Learn more about our 2:1 retirement matching, healthcare plans with nationwide coverage including prescription drug coverage, three dental plans, a vision plan, flexible spending account, well-being programs, long-term disability, automatic life insurance, general legal services, three early childhood centers, time away from work and work-life programs to promote balance.  Learn more at hr.umich.edu/benefits-wellness

Application Procedure

To be considered, a cover letter and resume are required.  The cover letter must be the leading page of your resume and should:

  • Specifically outline the reasons for your interest in the position and
  • Outline your particular skills and experience that directly relate to this position.
  • For more information, and to apply, use the link found here

Starting salaries will vary depending upon the qualifications and experience of the selected candidate.

Salary: $68,462.00 – $89,000.00

Work Location: Ann Arbor Campus, Ann Arbor, MI

Full-Time Position

 

MICDE Director, Krishna Garikipati, wins USACM Fellow award

By | News, Uncategorized

Krishna Garikipati, professor of Mechanical Engineering and of Mathematics, and director of MICDE, has been granted a 2019 United States Association for Computational Mechanics (USACM) Fellows award for his work in developing numerical methods applied to strongly nonlinear problems in living and nonliving material systems.

The Fellows Award recognizes individuals with a distinguished record of research, accomplishment and publication in areas of computational mechanics and demonstrated support of the USACM through membership and participation in the Association, its meetings and activities. All recipients shall be members in good standing of USACM. Multiple awards may be given at two-year intervals.

MICDE to host NSF Computational Mechanics Vision workshop

By | News

In Fall 2019, MICDE will host the NSF workshop entitled Computational Mechanics Vision Workshop. Organized by Boston University, Duke University and the University of Michigan, the workshop’s aim is to solicit and synthesize directions for computational mechanics research and education in the United States over the next decade and beyond from a diverse cross section of scientists and engineers.  Read more…

 

Introducing the new Clare Boothe Luce Graduate Fellows at the University of Michigan

By | Feature, News

The Michigan Institute for Computational Discovery and Engineering is pleased to announce the recipients of the Clare Boothe Luce graduate fellowships at the University of Michigan. Jessica Conrad, MS, currently an internee at LLNL, and Elizabeth Livingston, MS, a graduate of the University of Illinois, Urbana-Champaign, will be joining the University of Michigan in the Fall of 2019 to work towards their PhD. They were chosen because of their exceptional academic records and excellent preparation for graduate studies in computational sciences. Elizabeth will join the Mechanical Engineering department in the College of Engineering, and Jessica will join the Applied and Interdisciplinary Mathematics program in the College of Literature, Sciences and the Arts. As required by the fellowship, both students will enroll in the joint PhD in Scientific Computing program.

Elizabeth Livingston, Clare Boothe Luce Fellow at the University of Michigan

Elizabeth Livingston completed a BSc in Engineering Mechanics (with a minor in Computational Science and Engineering) and a MS in Mechanical Engineering at the University of Illinois, Urbana-Champaign. Elizabeth will join Prof. Garikipati’s research group in Mechanical Engineering. Elizabeth will carry out research in computational modeling of biomedical engineering problems. Of particular interest to her is the growth and remodeling of the cardio-vascular system. She will apply cutting-edge techniques of data-driven computational modeling to this topic using principles of scientific computing, including machine learning, uncertainty quantification, and finite element methods.

Elizabeth has a strong academic background, thriving while performing research in fields where women are underrepresented. Her ambition is to become a university faculty member, doing research in computational science. She looks forward to collaborating with colleagues and working with students to help them to succeed as others have helped her.

Jessica Conrad has a BS in mathematics and public health, a master’s in biostatistics, and an excellent track record of computational research both in her training and current work at Los Alamos National Laboratories. This background forms an ideal foundation for blending computing and mathematics in her PhD work, which will enable her to build a successful career in STEM. Jessica’s proposed area of study is in inverse problems in mathematical epidemiology, particularly focused on using computational and mathematical methods to gain useful insights into public health problems. A critical part of this work will include developing computational approaches to parameter identifiability. Conrad plans to work with Prof. Marisa Eisenberg, an expert in identifiability and infectious disease modeling, as one of her two primary co-mentors in the AIM program.

Jessica Conrad, Clare Boothe Luce Fellow at the University of Michigan

The Clare Boothe Luce program is funded by the Henry Luce Foundation. The program was created by Clare Boothe Luce, with the goal of increasing the participation of women in the sciences, mathematics and engineering at every level of higher education. It also serves as a catalyst for colleges and universities to be proactive in their own efforts toward this goal. At the University of Michigan, the program aims to increase women’s participation in the scientific computing community by recruiting top-of-the class women into the PhD in Scientific Computing program. The program is designed to allow the fellows to focus on their academic success by funding their first 3 years in the PhD, freeing them to try high-risk, innovative research projects in a unique interdisciplinary program, with ample networking opportunities and career support.

Research Opportunity, Mechanical Engineering, TREE Lab – Summer 2019

By | Educational, Research, SC2, SC2 jobs

Dr. Bala Chandran’s Research Group, Mechanical Engineering, TREE Lab

Dr. Bala Chandran is seeking a highly motivated graduate (doctoral or masters) student interested in
doing research in the broad area of understanding radiative heat transfer in granular and
suspension flows via computational modeling for applications of high-temperature
energy storage and catalysis applications. Applicants are expected to have a sound
knowledge of fluid/continuum mechanics and the fundamentals of heat-transfer;
experience in complex fluids or multiphase flows is desirable, though not essential.
Applicants should be interested in the computational aspects of this project to develop
and write code.

Qualifications

  • Strong analytical and computational skills, and intellectual independence (i.e.,
    able to read books and papers and learn by oneself; able to apply theoretical
    knowledge to practical situations)
  • Relevant course work and experience related to
    • Undergraduate level fluid mechanics, solid mechanics, heat transfer,
      radiation, numerical methods and programming, computational fluid/solid
      mechanics
    • Graduate level courses on any/all of the above topics will be a plus point
  • Excellent professional and work ethic
  • Team player that is ready to interface with people developing experiments on
    this project

Application Procedure

If you are interested in this opportunity, please email Prof. Bala Chandran
(rbchan@umich.edu) all the following documents AS SOON AS POSSIBLE:

  1. A 2-page CV with references listed
  2. Unofficial academic transcript
  3. 1 one-page (maximum) statement of interest that explains why you are best suited for working on the proposed research topic and indicates how you meet the required project criteria.
  4. Slides (maximum 5) that showcase your research experience and contributions

PhD student opening in Global Ocean Modeling and Scientific Computing

By | Educational, SC2 jobs

A PhD student is sought for a Department of Energy (DOE)-funded project in Global Ocean Modeling and Scientific Computing. The student will work with Professor Brian Arbic at the University of Michigan (U-M), Dr. Phillip Wolfram and Dr. Andrew Roberts of DOE’s Los Alamos National Laboratory, and other DOE scientists. The student will be admitted to the PhD program of the Department of Earth and Environmental Sciences, and will attain a joint PhD in U-M’s Program in Scientific Computing.

Project Description

The project involves insertion of tides into the ocean component of the DOE Energy Exascale Earth System Model (E3SM). The ocean component is based upon the Model Prediction Across Scales (MPAS) code, which uses a finite-element mesh to focus attention on coastal regions. With the addition of tidal forcing, the model will be an ideal tool with which to quantify the changes likely to occur in coastal areas over the next 50-100 years. The student will be strongly encouraged to spend significant time in Los Alamos, working alongside DOE scientists. The project is ideal for students who wish to apply the tools of scientific computing to societally relevant problems, in a university-DOE partnership with significant networking and travel opportunities. The project will increase the number of professionals familiar with both oceanography and computational science, an identified need in several federal ocean modeling centers including Los Alamos National Laboratory.

Application Procedure

  • Applicants must have strong quantitative and programming skills. Backgrounds in mathematics, computer science, physics, and related fields will be given highest consideration.
  • The preferred start date is January 1, 2020, but a start date of September 1, 2020 is also possible.
  • Students interested in applying to work with Professor Arbic should email their CV, unofficial transcript and cover letter, combined into a single PDF file to: Arbic-Ocean-Modeling-PhD@umich.edu. Questions about the project may also be sent to this email address.
  • In addition, an application to the PhD program in Earth and Environmental Sciences is required. See the Department website for application information. The application deadline to start in January 2020, is September 15, 2019. The application deadline for Fall 2020 is January 7, 2020.

The University of Michigan is an equal opportunity employer and is supportive of the needs of dual career couples. Women and minorities are encouraged to apply

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 https://womeninhpc.org/2019/03/mentoring-programme-2019/

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 https://arc.umich.edu/whpc/

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…