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 such as Hadoop and Spark and will be presented using the Wide Area Classroom (WAC) training platform.

When: Wed., February 16 @ 11:00 a.m. – 5:00 p.m. E.S.T. & Fri., February 18 @11:00 a.m. – 5:30 p.m. E.S.T.

Registration closes on February 14, 2022. Space is limited.

Tentative Agenda

Wednesday, February 16
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, February 18
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

An Academic and Research Career Workshop for Women in Computational and Data Sciences

By | Educational, Events

The Oden Institute for Computational Engineering and Sciences at UT Austin, Sandia National Laboratories (SNL), and Lawrence Livermore National Laboratory (LLNL) are partnering to host Rising Stars in Computational and Data Sciences, an intensive workshop for women graduate students and postdocs who are interested in pursuing academic and research careers.

The workshop will be held on April 20-21, 2022, in Albuquerque, NM.

The organizers are seeking nominations for outstanding candidates in their final year of PhD or within three years of having graduated. Approximately 30 women will be selected to come to Albuquerque for two days of research presentations, poster sessions, and interactive discussions about academic and research careers, with financial support for travel provided.

The nomination form requires (1) a letter of nomination and (2) a copy of the nominee’s resume.

Full details, including the nomination form and highlights from previous events can be found here.

Please consider nominating one of your outstanding current/recent PhD students or postdocs.

Nominations are due February 18, 2022.

Helmholtz Information and Data Science Academy Visiting Researcher Grant

By | Educational, SC2 jobs

Are you a doctoral researcher or Postdoc and your research has a strong link to the (applied) data and information sciences? The Helmholtz Visiting Researcher Grant offers doctoral students and Postdocs the opportunity to do a fully-funded short-term research stay (1 – 3 months) at one of the 18 Helmholtz centers. With more than 43,000 employees and an annual budget of 5 billion euros, Helmholtz is Germany’s largest scientific organization. Its research fields include: Energy; Earth and Environment; Health; Aeronautics, Space and Transport; Matter, and Information.

The Helmholtz Visiting Researcher Grant is promoted by HiDA, the Helmholtz Information and Data Science Academy. Its aim is to enable new research collaborations, to foster knowledge exchange, and to explore new or emerging research topics in the field of information and data sciences. The program addresses researchers in both academia and in industry. It offers researchers the opportunity to get to know the Helmholtz Association of German Research Centers.

Next Application Deadline: 15 March, 2022

For more information: https://www.helmholtz-hida.de/en/new-horizons/helmholtz-visiting-researcher-grant/

Info Session on the Program (via Zoom) on Tuesday, 18 January, 2022, 14.00 – 15.00pm  CET

Sign up here: https://tms.aloom.de/info-session-hida-research-grants-/

Postdoctoral position in neuroscience in the Renart Lab, Champalimaud Foundation, Portugal

By | Educational, SC2 jobs

The Renart Lab, in the Champalimaud Centre for the Unknown (Lisbon, Portugal), is looking for candidates for a postdoc position in within a project whose goal is to understand the neural basis of simple sensory judgements using modern methods in system’s neuroscience together with theory.

Successful applicants are expected to have experience studying controlled behavior in rodents using recordings and perturbations. The project has a strong quantitative component, so experience on computational neuroscience and statistics/machine-learning methods for behavioral and neural data analysis will be highly valued.
Some recent publications and methodologies relevant for the project are:
The Champalimaud Neuroscience Programme is a vibrant research community focussed on understanding the links between neural activity and behavior. The Renart lab promotes a horizontal and collaborative environment. The position offers a competitive salary and is available immediately for a duration of 3 years (with flexibility).

Interested applicants should send their CV, a brief motivation statement and the names of at least 2 references by email to:
careers@research.fchampalimaud.org and alfonso.renart@neuro.fchampalimaud.org

Flagship Pioneering Summer Fellowship Opportunity Information Session

By | Educational, SC2 jobs

Flagship Pioneering is a life science venture creation firm based out of Cambridge, MA. Flagship’s unique venture creation process is behind companies such as Moderna, Rubius Therapeutics, Indigo Agriculture, and several dozen others.

The Flagship Pioneering Summer Fellowship Program is a one-of-a-kind opportunity to work alongside scientist-entrepreneurs at the earliest stage of ideation and develop the next breakthrough life science companies. Over the course of an immersive 12-week paid program, you will be exposed to our proprietary innovation process, connect with scientific and business leaders within our vast ecosystem, and assess employment opportunities.

Ideal candidates are creative Ph.D., M.D., M.S., or science-oriented M.B.A. students that are within 1 year of graduating upon starting the fellowship or have recently graduated. Applications are rolling, but interested candidates are strongly encouraged to apply before January 31, 2022. 

During the 1-hour information session, you will learn about Flagship Pioneering from Associates Ayse Muñiz, PhD (University of Michigan Class of 2021), and Rahi Punjabi who will discuss a new AI Fellows track launching this summer. Those with a strong background in computer science, statistics, applied mathematics, physics, and computational biology are encouraged to attend to learn more about this new track.
 
DateThursday, January 13, 2022
Time: 11AM-12PM

Zoom info: https://flagshippioneering.zoom.us/j/96455167438?pwd=eWYxOURrZXkveUY3VHlMTnl6ZW9Gdz09&from=addon

Password: 756102

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.

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.

Idaho National Laboratory (INL) Graduate Fellowship Program

By | Educational, SC2 jobs

Idaho National Laboratory is now accepting applications for the INL Graduate Fellowship program. This program is designed to identify exceptional graduate students in research areas aligned with INL’s strategic agenda to enable the current and future mission of the lab. A collaboration between INL and universities, the INL Graduate Fellowship program provides mentoring and financial support for outstanding students who are enrolled, or plan to enroll, in graduate degree programs. Selected students will receive a salary of $60,000/year, plus tuition coverage from INL.

Flyer: INL_Graduate_Fellowship

How to apply

Applicants are invited to apply online through inl.gov/careers job posting numbers 16803 (for applicants in the fields of nuclear energy and clean energy development) and 16806 (for applicants in National & Homeland Security). Letters of recommendation should be submitted via email to graduatefellowships@inl.gov.

Important dates

  • February 13, 2022 – posting closes
  • May 2022 – selections will be announced

Fall 2021 Information Sessions

By | Educational, Events

Fall 2021 information sessions on graduate programs in computational and data sciences at U-M

U-M graduate students interested in computational and data sciences are invited to learn about joint programs that will prepare them for success in computationally intensive fields. The programs are organized by the Michigan Institute for Computational Discovery & Engineering, and the Michigan Institute for Data Science. Both institutes offer vast training and networking opportunities, including webinar series, symposia and student centered events.

Two sessions are scheduled

The sessions will address:

  • The Graduate Certificate in Computational Discovery and Engineering: trains students in computationally intensive research so they can excel in interdisciplinary HPC-focused research and product development environments.

  • The Graduate Certificate in Data Science: focuses on developing core proficiencies in data analytics: modeling, technology and practice.

  • The Graduate Certificate in Computational Neuroscience: provides training in interdisciplinary computational neuroscience to students in experimental neuroscience programs, and to students in quantitative science programs, such as physics, biophysics, mathematics and engineering.

  • The  Ph.D. in Scientific Computing: open to all Ph.D. students who will make extensive use of large-scale computation, computational methods, or algorithms for advanced computer architectures in their studies. It is a joint degree program, with students earning a Ph.D. from their current departments, “… and Scientific Computing” — for example, “Ph.D. in Aerospace Engineering and Scientific Computing.”

University of Michigan’s Ph.D. in Scientific Computing: A history of supporting research through education

By | Educational, Feature

#Computationalscience everywhere!

Left side, 2167 configuration console for the IBM/System 360 Model 67-2 (duplex) at the University of Michigan, c. 1969 [Picture by Scott Gerstenberger – Scott Gerstenberger, Public Domain]

The University of Michigan’s joint Ph.D. program in Scientific Computing recently achieved a record enrollment of 137 students. Between 2015, when 15 students were enrolled -mainly from the Colleges of Engineering and Literature, Science and the Arts- and today, the program has witnessed an explosive growth of interest on the part of U-M students. The program now has students enrolled from over 30 departments spanning 8 different schools and colleges, and more than 130 students have graduated in the last 31 years, including 17 students to-date in 2020.

This popularity is emblematic of the dominant role that computation plays in the world today. With the breakneck pace at which new hardware and software architectures are being developed, the boom in simulation-based research in a growing number of disciplines, and the initiatives in data and computational sciences implemented at U-M in the last few years, including the establishment of the Michigan Institute for Computational Discovery & Engineering, and the Michigan Institute for Data Science (MIDAS), it may seem only natural that scientific computing should attract this level of interest. However, like all exceptionally successful undertakings, it owes a great deal to its past. We reached back more than three decades to piece together the history of the Ph.D. in Scientific Computing at U-M.

The broader history of computational science and high performance computing at the University of Michigan is rich and extensive. U-M has been at the forefront of Cyberinfrastructure research for many decades, marked by the acquisition of U-M’s first virtual memory computer in 1967, an IBM 360/67, one of the first computers of its kind in the world. This milestone was followed by many others, including further hardware acquisitions and establishment of new units to support advanced research computing. An important early step was taken in 1985 when the College of Engineering established the Laboratory for Scientific Computation (LaSC). LaSC’s goal was to foster and promote the use of scientific computation in research and instruction at U-M. During those years, several reports from national study committees established computational science as the third pillar of scientific methodology, along with theory and experimentation. Faculty members of LaSC, who were at the forefront of driving these trends  recognized that any initiative in this field needed to include a robust student training program. 

left: Prof. Kenneth Powell (Aerospace Engineering), director of the Ph.D. in Scientific Computing program since 2005; right: Prof. William Martin (Nuclear Eng. and Rad. Sciences), director of the program from 1989 to 2004.

Prominent at that time in LaSC were Prof. William “Bill” Martin (Nuclear Engineering and Radiological Sciences – NERS), the laboratory’s director, Prof. John Boyd (Atmospheric, Oceanic and Space Sciences), the laboratory’s associate director, and Prof. Edward Larsen (NERS), who was hired as part of the College of Engineering’s initiative to move aggressively in the area of scientific computing. Together, they designed a graduate academic program with the goal of giving students a more comprehensive training in numerical analysis and computer science than is typically possible within standard disciplinary programs housed within individual departments and schools. The fundamental idea was that, to excel in computational science and engineering, one must have a thorough understanding of the mathematical and physical problems to be solved, expertise in  the methodologies and algorithms, and a foundation in computer science to be able to apply this arsenal of techniques on modern computer platforms. The need for a thorough understanding of the physical problems led directly to the requirement that students had to be enrolled in a traditional Rackham degree program (i.e., a home department), while the need for mathematical underpinning and knowledge of algorithms and computer science topics led to the requirements for courses in numerical analysis, parallel algorithms, and related topics. The PhD in Scientific Computing program was approved by the State of Michigan in 1988, and enrolled its first students in 1989. This was well in advance of a wider recognition of the centrality of computation in academia and industry. It is true today, as it was in 1988, that students can apply to the PhD in Scientific Computing program from any Rackham-recognized PhD program at the UM. This unique and flexible administrative structure has enabled the rapid growth experienced in recent years as scientific computing has become an indispensable tool in many fields of academic endeavor. 

Prof. Quentin Stout, director of the Center for Parallel Computing 1992-2001 [Picture source: NASA Insights 1998]

The oversight of the degree program has evolved over the years as administrative structures around scientific computing have shifted. Regardless of its administrative home, the program has always been organized under the Rackham School of Graduate Studies. Originally, the College of Engineering had oversight of the program, with Prof. Martin appointed as director, and with guidance from the LaSC Education Committee. This setup continued through the merger of LaSC and the Center for Parallel Computing1 into the Center for Advanced Computing in 2001. In 2005, Prof. Kenneth Powell (Aerospace Engineering) was named director of the program succeeding Prof. Martin, and has continued in the role since. In 2008, the Office of Research Cyberinfrastructure (ORCI) was established, and the oversight of the program changed to the U-M Office of Research. In 2013, when ORCI was re-named as Advanced Research Computing, and the Michigan Institute for Computational Discovery & Engineering (MICDE) was born, oversight was transferred to MICDE.

Since its inception, the program has been described as intended for students who will make intensive use of large-scale computation, computational methods or algorithms in their doctoral studies. Although the requirements and goals of the program have not  changed in 31 years, the research applications, the algorithms and methodologies, and the computer platforms have been in constant evolution. Naturally, the courses offered in support of the program have followed closely. In 1989 the core research areas behind the program were computational fluid dynamics, advanced computer architectures, and particle transport, with the majority of the students coming from engineering, and mathematics. Still, students working in areas where computation was less recognized, such as AIDS transmission or social research projects, also were enrolled. Over the next two decades, the tremendous increase in simulation-based research by the faculty in engineering and physical sciences added many other focus areas, including material science, astronomy, and high energy physics, to name just a few. This growth added a new driver as data-intensive research gained importance in those fields. 

Prof. Suzanne Weekes, Associate Dean of Undergraduate Studies, ad interim, and Professor of Mathematical Sciences at Worcester Polytechnic Institute (U-M 1995, Mathematics and Scientific Computing) [Picture source: SIAM News Sept. 2020]

Several faculty members have had an important role shaping the program, by offering fundamental courses and providing mentorship. Notably, Prof. Quentin Stout, from Computer Science and Engineering, has had a prominent role in the program. He was the founding director of the Center for Parallel Computing, which  provided the basis for subsequent units in this sphere at U-M. He also developed, and has been teaching, Parallel Computing since 1985, innovating its curriculum to remain at the cutting edge of the current techniques, important aspects of which have been based on his own research. Other foundational courses, such as the Department of Mathematics’ Numerical Methods for Scientific Computing I & II and Numerical Linear Algebra have been offered for more than 30 years. More recently the Department of Physics course, Computational Physics, and the College of Engineering course, Methods and Practice of Scientific Computing, along with an array of courses in machine learning, have played prominent roles in transforming the curriculum in scientific computing as research in these areas has likewise redefined the field.

Unsurprisingly, the Ph.D. in Scientific Computing has produced many exceptional alumni. The first student graduated from the program in 1992, and notably for its time, two of the first four graduates were women, when gender imbalance was barely recognized. A majority of the program graduates went on to  positions in academia or the National Laboratories, with the rest working in varied fields in industry or government. Some of these outstanding alumni include Suzanne Weekes, U-M 1995 (Mathematics and Scientific Computing), currently Associate Dean of Undergraduate Studies, ad interim, and Professor of Mathematical Sciences at Worcester Polytechnic Institute. Prof. Weekes has recently been named SIAM executive director, and will start her new role on January 1, 2021.  Another alumna, Rona Oran, U-M 2014 (Space Science and Scientific Computing), is a computational plasma physicist at MIT and a member of the NASA team that is designing and planning a mission to the metal asteroid Psyche to be launched in 2020.

The current goal of the program is still founded on the original idea of strengthening the students’ foundations in methodology and computer science. The leadership of the program strives to bring computational science to more research fields, but importantly, aims to do so by enhancing diversity in the field. An important marker of U-M’s success on this front came in  2018 in the form of the Henry Luce Foundation’s award to the University of two Claire Boothe Luce Ph.D. fellowships for women to enroll in the Ph.D. in Scientific Computing. The program is committed to pursuing other such opportunities and creating an environment where students of all backgrounds and identities feel welcome and thrive.

1 In 1992 U-M was awarded a major equipment grant by the National Science Foundation to create a testbed of parallel computing architectures. The Center for Parallel Computing was established to operate the facility. The center installed and operated several different parallel computers over the years, including KSR-1, KSR-2, Convex Exemplar, SGI PowerChallenge, IBM SP2, and AMD and Apple clusters.

We welcome 15 students to the 2020-21 class of MICDE graduate fellows

By | Educational, News

MICDE is proud to announce the recipients of the 2020 MICDE graduate fellowships. The fellows’ research projects involve the use and advancement of scientific computing techniques and practices. From political science, psychology, physics, and applied and interdisciplinary mathematics within the College of Literature, Science & the Arts to aerospace engineering, mechanical engineering, materials science engineering, industrial & operations engineering, and civil & environmental engineering within the College of Engineering, the 2020 MICDE fellows epitomize the reach of computation in diverse scientific disciplines.

For the past six years, MICDE has awarded fellowships to over 120 graduate students from our large community of computational scientists. The MICDE graduate student top-off fellowship provides students with a stipend to use for supplies, technology, and other materials that will further their education and research. Among other things, awards have helped many to travel to conferences and meetings around the world to share the rich and diverse research in computational science being carried out at U-M.

The awardees are:

Eytan Adler, Aerospace Engineering
Hessa Al-Thani,
Industrial and Operations Engineering
Zijie Chen,
Mechanical Engineering
Alexander Coppeans
, Aerospace Engineering
Xinyang Dong, Physics
Karthik Ganesan,
Psychology
Iman Javaheri, Aerospace Engineering
Huiwen Jia, Industrial and Operations Engineering
Daeho Kim, Civil and Environmental Engineering
Yudan Liu,
Chemistry
Emily Oliphant
, Materials Science and Engineering
Ryan Sandberg, Applied and Interdisciplinary Mathematics
Patrick Wu, Political Science
Zhucong Xi, Materials Science and Engineering
Yi Zhu, Civil and Environmental Engineering

Learn more about the fellows and the MICDE Fellowship program