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Luis W. Alvarez Fellowship in Computing Sciences

Berkeley Lab’s Luis W. Alvarez Fellowship in Computing Sciences offers upcoming or recent Ph.D.s the opportunity to work on some of the most important research challenges in computing sciences at a national lab synonymous with scientific excellence. Since its founding in 2002, the Alvarez Fellowship has cultivated exceptional young scientists who have made outstanding contributions to computational and computing sciences as researchers, professors, and in the private sector.

Alvarez Fellows apply the latest technologies to computational modeling, simulations, and advanced data analytics for scientific discovery in materials science, biology, astronomy, environmental science, energy, particle physics, genomics, and other scientific domains. Working in a stimulating environment, they present results at major conferences and establish strong connections to academic and industry partners. They receive competitive salaries, relocation assistance, excellent benefits, frequent travel opportunities, and an opportunity to work in the San Francisco Bay Area.

This fellowship is awarded for two years with the possibility of a third by renewal. Upcoming or recent Ph.D. graduates in computational science disciplines, computer science, or applied mathematics who have received their degrees within the last three years are encouraged to apply.

Launched in 2002, the Alvarez Fellowship is supported in part by the DOE Office of Advanced Scientific Computing Research applied mathematics program and Berkeley Lab’s Laboratory Directed Research and Development program.

If you have a Ph.D. in computer science, mathematics, or any other computational science discipline granted in the past three years, we encourage you to apply. As a prospective fellow, you should be well-versed in advanced algorithms, software techniques, HPC systems, and/or networking in a related research field. Applicants should have demonstrated creativity and the ability to perform independent research. We are also looking for excellence in a related research field, including a solid publications record, high citations, and awards.

In addition to a standard job application, prospective fellows should also submit the following:

  1. CV or resume with publications list included as one document
  2. Cover letter
  3. Brief research statement
  4. List of three references who can provide letters of recommendation

List of references must include contact information for each person. The Fellowship hiring committee will reach out to the references, who will submit their letters of recommendation directly to Berkeley Lab.

For over 20 years, the Alvarez Fellowship program has helped polish and launch promising postdocs into fruitful careers in National Laboratories, research labs, academia, and industry. See where our fellows are now and read about where they started.

Alumni in Academia

Alexander Kemper, 2012
North Carolina State University Read Kemper’s Alvarez profile.
Didem Unat portrait
Didem Unat, 2012
Koç University, Istanbul
Read Unat’s Alvarez profile.
Lin Lin portrait
Lin Lin, 2011
UC Berkeley / Berkeley Lab
Read Lin’s Alvarez profile.

Alumni at National Labs / Research Institutions

Julianne Mueller head and shoulders
Juliane Mueller, 2014
National Renewable Energy Lab (NREL)
Read Mueller’s Alvarez profile.
Aydın Buluç
Aydın Buluç, 2010
Berkeley Lab & UC Berkeley
Read Buluç’s Alvarez profile.

Alumni in Industry

George Pau, 2018
Alambic Investment Management, LP
Read Pau’s Alvarez profile.

Current Alvarez Fellow

As employees of Berkeley Lab, Alvarez fellows work in a research environment synonymous with scientific excellence. Sixteen Nobel prizes are associated with Berkeley Lab. Eighty Lab scientists are members of the National Academy of Sciences (NAS), seven of whom are computational scientists and applied mathematicians. Eighteen engineers have been elected to the National Academy of Engineering, four of whom work in the Berkeley Lab Computing Sciences area. Four Berkeley Lab researchers have received IEEE Sidney Fernbach Awards for being pioneers in the development and application of high-performance computers for the solution of large computational problems. Fifteen Berkeley Lab scientists have won the National Medal of Science, our nation’s highest award for lifetime achievement in fields of scientific research, and one received the National Medal of Technology and Innovation.

Berkeley Lab is also home to six Department of Energy (DOE) National User Facilities:

  • Advanced Light Source (ALS),
  • Energy Sciences Network (ESnet),
  • Joint Genome Institute (JGI),
  • National Center for Electron Microscopy (NCEM),
  • Molecular Foundry,
  • and National Energy Research Scientific Computing Center (NERSC).

These centers give thousands of researchers access to some of the most advanced tools in modern science, including light sources, supercomputers, high-speed networks, and nanoscience research facilities.

Whether running extreme-scale simulations on a supercomputer or applying machine learning or data analysis to massive datasets, scientists today rely on advances in and integration across applied mathematics, computer science, and computational science, as well as large-scale computing and networking facilities, to increase our understanding of ourselves, our planet, and our universe.

Berkeley Lab's Computing Sciences Area researches, develops, and deploys new tools and technologies to meet these needs and to advance research in our core capabilities of applied mathematics, computer science, and computational science. In addition to fundamental advances in our core capabilities, we impact such areas as materials science, chemistry, biology, astrophysics, climate change, combustion, fusion energy, high performance computing (HPC) systems, and network technology.

Some Computing Sciences research areas include the following:

  • Developing scientific applications and software technologies for extreme-scale and energy-efficient computing
  • Developing mathematical modeling for complex scientific problems
  • Designing algorithms to improve the performance of scientific applications
  • Researching digital and post-digital computer architectures for science
  • Advancing extreme-scale scientific data management, analysis, and machine-learning
  • Developing next-generation machine learning and AI approaches for science
  • Advancing quantum computing technologies, software, algorithms, and applications
  • Evaluating or developing new and promising HPC systems and networking technologies
  • Researching methods to control and manage dynamic circuit networks
  • Developing large-scale visualization and analytics technologies
  • Managing scientific data in distributed environments

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