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2016-2017 MICDE Research Snapshot

By | Research

2016-2017 has been a year of sustained growth for MICDE’s research portfolio. The number of faculty affiliated with the institute stands at 130, spanning 30 departments and eight schools and colleges. The Center for Scientific Software Infrastructure was established to bring together the U-M community engaged in developing open scientific software. It will focus on establishing best practices for developing, disseminating and documenting scientific software in the public domain. Led by Prof. Emanuel Gull (Physics), the Center aims to provide training and support for researchers that are ready to transform their research codes into well-engineered software. It offers grant support in the form of programmers, consultants, and administrative assistance. It includes a portal to share your code with the research community at large.

MICDE’s two established centers, the Center for Network and Storage-Enabled Collaborative Computational Science (CNSECCS) and the Center for Data-Driven Computational Physics (DaCoP), each held their first symposium, showcasing their first year of research activities. This included evidence of the growing reach of OSiRIS, the open framework for storage, computation and collaboration against big scientific data, and the first results from ConFlux, U-M’s groundbreaking computing cluster for data-driven computational physics. These results have been presented at several conferences, and are appearing in the leading computational journals.

Vorticity field at a late time in the evolution of an elliptic vortex patch computed by a Lagrangian particle method with remeshing and treecode-accelerated evaluation of the Biot-Savart integral. (source: Ling Xu)

MICDE also funded its first round of Catalyst Grants, that are supporting four innovative computational science research projects. Research funded by the Catalyst Grants is breaking new ground, while helping define the future of computational science. This research consists of:

  • studies of the neuronal dynamics of learning and memory formation;
  • new algorithms for the complex, nonlinear dynamics of power grids;
  • novel integral equations methods using recent advances in numerical analysis;  
  • and probabilistic computational frameworks for rare but often catastrophic events.

The past academic year MICDE hosted 14 external speakers with backgrounds and research concentrations that span the breadth of computational science of today and the future. The series culminated in MICDE’s annual symposium: “The New Era of Data-Enabled Computational Science,” which featured talks by worldwide leaders in computational science, including U-M faculty. The symposium included a student poster competition with over 50 entries.

Dr. Ann Almgren from the Lawrence Livermore National Lab speaking about Next Generation AMR, part of the 2016-2017 MICDE Seminar Series

MICDE faculty are committed to growing the already strong U-M community of computational scientists. Over the past year, as before, we have organized a number of workshops to foster collaboration and put together interdisciplinary teams in response to funding calls from federal agencies and foundations.   MICDE offers faculty teams institutional support and direct links to our excellent educational programs as well as cyberinfrastructure, all of which strengthen faculty proposals. With the backing of our parent unit, Advanced Research Computing (ARC), and its technical and consulting services (ARC-Technology Services, and Consulting for Statistics, Computing and Analytics Research), this effort has raised over $22M in external funding over the past 2 years. This includes support from federal agencies (NSF, NIH, and DOD), as well as from industry.  We also work with the academic units at U-M to identify compelling new areas for recruiting the type of faculty members who will drive computational science in the future.

 

2016-2017 Education Snapshot

By | Educational, General Interest, News

Over the past year, MICDE’s educational programs and activities have experienced tremendous growth. The Graduate Certificate in Computational Discovery and Engineering currently has 50 students enrolled, spanning 19 departments from 5 different schools and colleges. Sixteen students graduated within the last academic year, and 44 have graduated since the Graduate Certificate was established in 2013. Even further, the number of women in the program went from zero in 2014 to 15 currently enrolled.

The Ph.D. in Scientific Computing has experienced extraordinary growth, with 74 students enrolled from 20 departments, and four schools or colleges. We added a section to our web site with both programs’ alumni information.

We are working to broaden as well as to deepen the activities and resources available to students in both programs. Twenty MICDE fellowships were awarded this academic year to students in our programs. We continued to sponsor student software teams at competitions, as well as individual students presenting their work at leading conferences. On-campus, MICDE student activities include networking lunches, and the Scientific Computing Student Club (SC2). On the programmatic front, our non-engineering students now have access to a CAEN account that gives them more options to connect and use U-M High Performance Computing resources. Relevant grant opportunities for students are tracked and updated in MICDE’s grant webpage

2016-2017 MICDE Fellow Yuxi Chen (ClaSp) presenting his work at the MICDE Annual Symposium

Several educational projects and initiatives are afoot at MICDE, including a Massively Open Online Class (MOOC) in Computational Thinking targeting both high school students and their teachers. This MOOC aims to introduce learners to algorithmic approaches to problems. This initiative is being developed in collaboration with the School of Education, the office of Academic Innovation, and with input from a number of high schools in the Detroit Metropolitan Area.The two new courses launched by MICDE faculty last year, Methods and Practices of Scientific Computing, and Data-Driven Analysis and Modeling of Complex Systems, were successful in their first offerings during the 2016-2017 academic year, and are being offered again in 2017-2018. Other teams of MICDE faculty are at work across campus to develop new courses in computational science.

2016-2017 Outreach and Industrial Engagement Snapshot

By | General Interest

2017 miRcore’s GIDAS Biotechnology Summer Camp participants

Community Outreach

MICDE remains committed to advancing the understanding of science in general, and computational science in particular, in the community. To this end we have continued our support of internal and external organizations. Externally, our ongoing support of the non profit science outreach group, miRcore, included running MICDE sponsored compute cycles on Flux for high school students participating in miRcore’s computational biology summer camps through their student network called GIDAS. We also continued to support the undergraduate Biosoftware Team that has competed in the International Genetically Engineered Machine (iGEM) year competition for the past five years. The team participates in the software track aimed for computer scientists and developers to nurture their knowledge of biology, and for computational biologists, bioinformaticians and biologists to enhance their aptitude for building software. Over the past couple of years, the team has been developing ProtoCat, a software developed to address the issue of reproducibility in synthetic biology. It is a collaborative platform on which researchers share their experiment protocols and users can customize them to meet their own needs. For the third year in a row, the team returned with a gold medal.

2017 BioSoftware Team

Internally, less than two years since its inception, the Scientific Computing Student Club (SC2) has established several activities that complement the formal training in computational science available at U-M, including through MICDE’s PhD in Scientific Computing, and Graduate Certificate in Computational Discovery and Engineering. Over the past year, the SC2 had his own invited speakers, organized tours to the Flux facility and the U-M 3D Lab, organized the first Visualization Challenge, co-sponsored by NVIDIA, and just recently added a section on its web page for academic and non-academic job opportunities. During the 2017 Fall Term, SC2 students ran a weekly Machine Learning Collaborative Workshop, and the group is planning a hands-on series on code parallelization.

Industrial Engagement

We continue working towards increasing our engagement with industry. Over the last two years, in addition to NVIDIA, MICDE has established partnerships with IBM, through the joint design and development of our computer cluster, ConFlux, and with Toyota Research Institute, through a funded project on scientific software for materials research. We are now working in partnership with the U-M Business Engagement Center to create an MICDE industrial affiliates program, which will provide many additional avenues for interaction between our students or faculty and industry.

 

 

 

[SC2 Jobs] Machine Learning Scientist for Toyota Research Institute of North America

By | SC2 jobs

Toyota Research Institute of North America, located in Ann Arbor, Michigan, is seeking a machine learning scientist to support the in-house research activities. This individual will join a team responsible to develop state-of-art methodologies for material informatics. The position requires staying abreast of emerging field of machine learning, performing original research, publishing/presenting results, involve in collaborative research. Candidate must be able to work effectively with a diverse group of scientists.
The position is subject to annually contract renewal.

Key Responsibilities:
• Develop machine learning models to deal with problems/challenges in material informatics;
• Establish tools to collect and structure materials data and harvest valuable information
subsequently;
• Perform text mining from scientific literatures and internal technical documents;
• Frequently communicate with materials scientist within the organization;
• Effectively respond to the challenges emerging in materials project;
• Regularly report and present to the research team and managements;

Minimum Requirements:
• MS or above degree in Computer Science, Statistics or related technical field or equivalent
practical experience;
• Strength with machine learning and text mining techniques;
• Fluency in programming languages (Python, C/C++, Java);
• Hands-on experience with statistical software (R, SAS, Matlab, Python);
• Strong verbal and written communication skills;
• Self-motivated, intelligent individual with initiative and drive for overcoming technical
challenges;

Preferred Requirements:
• Experience with deep learning techniques;
• Experience in projects related to materials science, chemistry and physics;
• Established capability in scientific writing and presentation;

 

The applicant should send the resume to chen.ling@toyota.com before February 9, 2018.

Job category

Machine Learning Scientist

Location

Ann Arbor, MI

Application deadline

February 9, 2018

[SC2 Jobs] Stephen Timoshenko Distinguished Postdoctoral Fellowship at Stanford University

By | SC2 jobs

 

 

 

 

The Mechanics and Computation Group (Department of Mechanical Engineering) at Stanford University is seeking applicants for the “Stephen Timoshenko Distinguished Postdoctoral Fellowship.” This appointment is for a term of two years, beginning in September 2018.

The Stephen Timoshenko Distinguished Postdoctoral Fellow will be given the opportunity to pursue independent research in the general area of solid mechanics, as well as to contribute to ongoing research in the Mechanics and Computation Group. Research activities should be in the field of solid mechanics interpreted broadly, including areas such as additive manufacturing, micro- and nano-mechanics, bio-mechanics, and related research directions such as applications of machine learning. Candidates will be given opportunities to develop their teaching experience by designing and teaching a class in the mechanics curriculum. This position might be of particular interest to candidates who are seeking an academic career.

Candidates are expected to show outstanding promise in research, as well as strong interest and ability in teaching. They must have received a Ph.D. prior to the start of the appointment, but not before 2016. Applicants should send a cover letter (one page); a curriculum vitae; a list of publications; brief statements of proposed research (up to three pages) and teaching (one page); the names and contact information of three recommendation letter writers.

For full consideration, applications must be completed no later than 11PM PST, Sunday March 4, 2018. However, applications will continue to be accepted until the position is filled.

Stanford is an equal opportunity employer and all qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by law. Stanford also welcomes applications from others who would bring additional dimensions to the University’s research and teaching missions.

Please send your application by email to:
Norma Costello, normac@stanford.edu, 650 723-4133
Email subject: Stephen Timoshenko Distinguished Postdoctoral Fellow search
All documents attached to the email should be PDF (Portable Document Format).

For updates see https://mechanics.stanford.edu/hiring.

 

Job category

Postdoctoral Fellowship

Location

Stanford University

Application deadline

No later than 11 p.m., Sunday, March 4, 2018