Luis W. Alvarez Postdoctoral Fellowship and Admiral Grace M. Hopper Postdoctoral Fellowship

Luis W. Alvarez Postdoctoral Fellowship and Admiral Grace M. Hopper Postdoctoral Fellowship in Computing Sciences

Recruitment began on September 2, 2025

and the job listing Expires on March 2, 2026

Researchers in computer science, mathematics, data science, or any computational science discipline who have received their Ph.D. and have completed no more than three years of postdoctoral work are encouraged to apply. Only one (1) application is needed, and it will be considered for both postdoctoral fellowships.

The successful candidates will participate in research activities in computer science, mathematics, data science, or any computational science discipline of interest to the Computing Sciences Area and Berkeley Lab. Alvarez Fellows apply advances in computer science, mathematics, computational science, data science, machine learning or AI 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.

Hopper Fellows concentrate on the development and optimization of scientific and engineering applications leveraging high-speed network capability provided by the Energy Sciences Network or run on next-generation high performance computing and data systems hosted by the National Energy Research Scientific Computing Center at Berkeley Lab.

Since its founding in 2002, Berkeley Lab’s Luis W. Alvarez Postdoctoral Fellowship (go.lbl.gov/alvarez) has cultivated exceptional early career scientists who have gone on to make outstanding contributions to computer science, mathematics, data science, and computational sciences. The Admiral Grace Hopper Postdoctoral Fellowship (go.lbl.gov/hopper) was first awarded in 2015 with the goal of enabling early career scientists to make outstanding contributions in computer science and high-performance computing (HPC) research.

About Computing Sciences at Berkeley Lab:

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, data science, and computational science.

In addition to fundamental advances in our core capabilities, we impact such areas as astrophysics and cosmology, accelerator physics, chemical science and materials science, combustion, fusion energy, nuclear physics, biology, climate change, and HPC systems and network technology. Research areas in Computing Sciences include but are not limited to:

• 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
• Developing and advancing extreme-scale scientific data management, analysis, and visualization
• Developing and advancing next-generation machine learning, AI, and data science approaches for science
• Advancing quantum computing and networking technologies, software, algorithms and applications
• Evaluating or developing new and promising HPC systems and networking technologies
• Researching methods to control and manage next-generation networks
• Managing scientific data and workflows in distributed environments

Qualifications:

• Requires a Ph.D. in computer science, mathematics, computational science, or related discipline.
• Candidates must have no more than 3 years of Postdoctoral Researcher or similar experience.
• Expertise with advanced algorithms, software techniques, HPC systems and/or networking in a related research field.
• Demonstrated creativity and the ability to perform…