Luis W. Alvarez Postdoctoral Fellowship in Computing Sciences
This fellowship provides recent graduates (within the past three years) opportunities to work on some of the most important research challenges in computing sciences—from the architecture and software of next generation high performance computing systems and networks, to mathematical modeling, algorithms, and applications of advanced computing, material science, biology, astronomy, climate change and other scientific domains.
As employees of Berkeley Lab, Alvarez fellows work in a research environment synonymous with “scientific excellence.” Thirteen Nobel prizes are associated with Berkeley Lab. Fifty-seven 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. And, 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.
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 facilities for studying the nanoworld.
Record of Excellence
Since its founding in 2002, Berkeley Lab’s Luis W. Alvarez post-doctoral fellowship has cultivated exceptional young scientists who have gone on to make outstanding contributions to computational and computing sciences.
Former fellows George Pau (‘07) and Anubhav Jain (’10) are making significant advances in their respective scientific fields using computing. As an Alvarez Fellow, Pau worked with Berkeley Lab Applied Mathematician, Computer Scientist and NAS member John Bell to develop adaptive schemes for reactive geochemical flow. Now, Pau is a computational scientist in Berkeley Lab’s Earth Sciences Division, working on high-performance computing, model reduction and optimization algorithms relevant to earth sciences. He is currently involved in several key DOE projects, including Advanced Simulation Capabilities for Environmental Management (ASCEM) and National Risk Assessment Partnership (NRAP).
Jain is currently focusing on new materials discovery using high-throughput computations. Scientific American called this emerging field one of “2013’s World Changing Ideas.” A research scientist/chemist in Berkeley Lab’s Electrochemical Technologies Group, Jain is involved in two major DOE projects, including Materials Project and Joint Center for Energy Storage Research (JCESR) battery hub. As an Alvarez Fellow in Berkeley Lab’s Computational Research Division (CRD), Jain created the FireWorks framework for automating calculations at supercomputing centers.
Meanwhile, former fellows Joshua Schrier (’05) and Kamesh Madduri (’08) have gone on to become professors, conducting their own research while training new generations of researchers. An Assistant Professor of Chemistry at Haverford College, Schrier teaches courses in physical and theoretical chemistry, and nanoscience. His current research focuses on organic semiconductors, organically-templated inorganic solids, and graphene nanostructures. As an Alvarez Fellow, he worked with Berkeley Lab’s Lin-Wang Wang to use high-performance parallel plane-wave pseudopotential density functional methods for the study of nanostructures.
An Assistant Professor in the Computer Science and Engineering department at Pennsylvania State University, Madduri teaches courses in concurrent scientific programming and concurrent scientific computing. His current research focuses on high-performance computing, parallel graph algorithms and massive scientific data analysis. He was honored with the SIAM Activity Group on Supercomputing Junior Scientist Prize in 2010 and a National Science Foundation (NSF) Career Award in 2013. As an Alvarez fellow, he worked under the guidance of Berkeley Lab’s Arie Shoshani on developing parallel graph algorithms and massive scientific data analysis.
Many Alvarez fellows choose to join the Berkeley Lab Computing Sciences community as career scientists. Lavanya Ramakrishnan (’09) recently worked in collaboration with Google to develop free models for assessing energy efficiency. A six-month study led by Ramakrishnan in 2013 found that moving common software applications used by 86 million U.S. workers to the cloud could save enough electricity annually to power Los Angeles for a year. As an Alvarez fellow, Ramakrishnan evaluated cloud computing technologies and infrastructure for scientific applications. Her findings were published in DOE’s widely anticipated 2011 Magellan Report on Cloud Computing for Science.
Recent alumnus Aydın Buluç (’10) is a rising star in DOE. In 2013, Buluç was honored DOE Early Career Award for his work on energy-efficient parallel graph and data mining algorithms. He will use this funding to explore methods to increase the energy efficiency of parallel algorithms and data mining tasks. He will also develop a new family of algorithms to drastically reduce the energy footprint and running time of graph and sparse matrix computations that form the basis of various data mining techniques. As an Alvarez fellow, Buluç’s research focused on high-performance graph analysis, libraries, and their applications in genomics and bioinformatics, parallel sparse matrix computations, and communication-avoiding algorithms.
Other fellows are applying their expertise to address challenges in industry. Former fellow Raquel Romano (’05) is a software engineer at Google, where she develops technology for first responders at Google’s Crisis Response Team.
Luis W. Alvarez:
A Legacy of Scientific Computing
Today's computational science is rooted in the efforts of innovative scientists like Luis W. Alvarez. In the 1950s, physicist Dr. Alvarez opened a new era in high-energy physics research with his proposal to build a pressurized chamber filled with liquid hydrogen. Known as a “bubble chamber,” this device would allow scientists to discover new particles and analyze their behavior. In his 1955 prospectus for such an experimental facility, Dr. Alvarez became one of the first scientists to propose using computing devices for analyzing experimental data, even before such computers were actually available.
By the 1960s, Dr. Alvarez's vision was reality. His colleagues at Berkeley Lab used computers to track some 1.5 million particle physics events annually and developed scientific computing techniques which were adopted by researchers around the world. This effort led to Dr. Alvarez receiving the Nobel Prize for Physics in 1968. We encourage those who share Dr. Alvarez's scientific curiosity and dedication to join us in our efforts by applying for a fellowship.
How to Apply
Current Alvarez Fellows
- Robert Saye — Mathematics Group (9-16-13)
- Alexander Kemper —Scientific Computing Group (9-30-12)
- Didem Unat —Advanced Technologies Group (5-30-12)
Previous Alvarez Fellows
- Lin Lin —Scientific Computing Group (09-22-11)
- Anubhav Jain — Scientific Computing Group (4-12-10)
- Aydın Buluç — High Performance Computing Research Department (4-12-10)
- Lavanya Ramakrishnan — Advanced Computing for Science Department (7-01-09)
- Aleksandar Donev — Center for Computational Sciences and Engineering (8-24-09)
- Kamesh Madduri — Scientific Data Management Group (8-18-08)
- George Pau — Center for Computational Science and Engineering (8-14-07)
- Rollin Thomas — Scientific Computing Group (10-22-07)
- Raquel Romano — Imaging and Informatics Group (2-24-05)
- Joshua Schrier — Scientific Computing Group (10-5-05)
- Caroline Gatti-Bono — Applied Numerical Algorithms Group (10-15-02)
- Andreas Adelmann, First Alvarez Fellow in Computational Science (5-29-02)