Bruno Rossi Distinguished Postdoctoral Fellowship

Mission Support and Test Services, LLC

$130K *
Aerospace & Defense
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • PhD in a STEM field awarded within 3 years or completed by the start date.
  • Proven excellence in high-performance scientific computing or accelerator physics.
  • Strong collaborative skills across diverse organizations.
  • Effective verbal and written communication skills.
  • Experience in independent and team-oriented work with minimal supervision.
  • Familiarity with modeling complex systems using machine learning and AI.

Responsibilities

  • Drive advancements in theory, computational modeling, and machine learning applications.
  • Lead research focused on accelerator and beam physics, including relativistic interactions and beam transport.
  • Develop models for collective effects and instabilities in particle acceleration.
  • Create diagnostics and inferential methods to extract critical machine parameters.
  • Optimize accelerator performance through advanced data-driven machine tuning techniques.
  • Implement predictive maintenance and anomaly detection mechanisms for accelerator systems.
  • Build digital twin architectures to integrate simulations and diagnostics.

Benefits

  • Research support up to $250,000 for R&D expenses over the fellowship term.
  • Dedicated mentorship from a senior NNSS scientist.
  • Opportunities to present research to leadership and publish in peer-reviewed journals.
  • Flexibility in start date and a potential three-year term based on performance.
  • Access to collaborative work with partner labs such as LANL and LLNL.
Full Job Description
Job Description

The NNSS Science & Technology Directorate invites exceptional early-career scientists to apply for the Bruno Rossi Distinguished Postdoctoral Fellowship. The Rossi Fellow will drive advances in the theory, computational modeling, and/or machine-learning applications to the Scorpius linear induction accelerator (LIA) - one of the Nation's flagship capabilities supporting NNSA missions. This is a high-impact, publication-friendly role embedded with a senior NNSS mentor and collaborating laboratories.

Fellowship Focus Areas (Theory/Computation/ML)

We are seeking exceptional early-career PhD scientists or engineers with expertise in accelerator physics and a passion for applying data science, artificial intelligence (AI), and machine learning (ML) to model, control, and optimize complex systems. We also welcome applicants with a strong background in computational science who are eager to apply their skills to challenges in accelerator science. In particular, fellows will be fully supported to lead a research program focused on one or more of the following areas.

A. Accelerator & Beam Physics (Theory/Computation)
• Relativistic Beam-Target Interaction Physics: Investigating beam interactions with complex bremsstrahlung converters, including X-ray source modeling, dose and fluence optimization, and converter survivability under advanced material responses.
• Beam Transport in Complex Environments: Studying beam transport in solenoidal and induction systems, with emphasis on emittance preservation, halo formation and mitigation, and energy spread control under realistic operating conditions.
• Collective Effects and Instabilities: Developing models and mitigation strategies for phenomena such as Beam Breakup (BBU), corkscrew motion, and transverse/longitudinal impedance-driven instabilities.
  • Pulsed-Power and Accelerator Coupling: Exploring circuit-beam co-simulation, magnet and induction module dynamics, and timing and waveform shaping to enhance stability and brightness.
  • Diagnostics by Design: Creating inference methods and synthetic diagnostics to extract critical machine parameters-such as emittance, current, energy, spot size, and centroid motion-from limited data, while incorporating uncertainty quantification and error budgets for machine studies.
    • Multiphysics Target Response: Modeling the Magneto-Hydrodynamics (MHD) and thermomechanics of converter materials under intense pulsed loading, including shock and thermal fatigue, to evaluate lifetime and performance trade-offs.

Representative tools and methods: Particle-In-Cell (PIC) and Vlasov-Fokker-Planck simulations, hybrid PIC-fluid models, envelope and moment techniques, Monte Carlo radiation transport, surrogate modeling, adjoint and gradient-based optimization, as well as rigorous uncertainty quantification (UQ) and sensitivity analysis.

B. Machine Learning, Artificial Intelligence, and Digital Twin Foundations for the Scorpius Accelerator
• Data-Driven Machine Tuning: Optimizing accelerator performance by leveraging cutting-edge methods to rapidly identify optimal set points and compensate for beam drifting across multiple shots and variable thermal states.
  • Predictive Maintenance and Anomaly Detection: Applying time-series modeling to pulsed-power components and beam diagnostics for fault prediction, remaining useful life estimation, and automated alert systems.
  • Physics-Constrained Machine Learning: Implementing novel neural network architectures and reduced-order modeling techniques, constrained by first-principles physics, to deliver fast and explainable predictions.
  • Uncertainty-Aware Control: Developing decision-making frameworks with calibrated posteriors to ensure safe operation, while building digital twin architectures and data pipelines that integrate simulation, controls, and diagnostics in near-real time.


Successful applicants will be expected to demonstrate a sophisticated understanding of these methodologies. This includes a meticulous selection of appropriate techniques, awareness of their inherent limitations.

Impact

This fellowship offers a distinguished opportunity to drive transformative innovation at the forefront of accelerator science. The Rossi Fellow will be instrumental in developing and demonstrating next-generation capabilities for the Scorpius accelerator and allied radiographic systems. This foundational work is critical for achieving enhanced brightness, stability, system responsiveness, and long-term reliability, directly reinforcing the strategic imperatives of NNSA's stockpile stewardship mission. The Fellow's research will provide a definitive basis for optimizing machine studies, informing strategic hardware development, and accelerating the realization of the full Scorpius digital twin

Application Materials

Please combine materials into a single PDF when possible:
  1. Curriculum Vitae (with education, publications, software contributions, and up to three references to key codes or datasets).
  2. Research Statement (≤ 3 pages): proposed 2-3 projects aligned to Focus Areas; include methods, anticipated milestones, and potential collaborators.
  3. Selected Publications or preprints demonstrating relevant expertise.
  4. References: contact information for 3-5 referees. (Letters may be requested at the shortlist stage.)

Interviews: Finalists will be invited for a two-day on-site interview, including a technical seminar on current work and proposed research.

How to Apply & Key Dates:
  • Deadline for full consideration: October 31, 2026, 11:59 PM Pacific Time
  • Interviews: November-December 2026
  • Decisions: January 2027
  • Start date: 2027 (flexible)

Compensation & Support
  • Annual salary: $130,000
  • Research support: Up to $250,000 across the term for R&D expenses as described above, allocated annually with NNSS mentor and program approval. Discretionary research support across the fellowship for hardware, software, data/storage, user facility access, travel, and-subject to policy and need-the ability to fund a graduate student or research associate.
  • Term & Support
    - Term: Up to 3 years (initial 2-year appointment with a 3rd-year extension based on performance and program needs).
    - Mentorship & Visibility: Dedicated NNSS mentor; opportunities to present to NNSS/NNSA leadership and partner labs (LANL, LLNL) and to publish in peer-reviewed venues consistent with program requirements.


About the Fellowship & Namesake

The fellowship honors Bruno Benedetto Rossi ([redacted]), a trailblazing experimental and theoretical physicist whose career helped shape modern particle physics, space plasma physics, and x-ray astronomy. Trained at the University of Bologna, and having collaborated with Niels Bohr in Denmark, Patrick Blackett at the University of Manchester, and Enrico Fermi at the University of Chicago, Rossi later became a professor at MIT. There, he pioneered the electronic coincidence method, which enabled unambiguous detection of rare, fast events and opened the door to modern high-energy instrumentation.

His early work established the charged nature of cosmic rays, mapped their latitude/altitude effects, and revealed extensive air showersproduced by ultra-high-energy primaries.

During the Manhattan Project, Rossi led diagnostic development at Los Alamos, including fast ionization chambers and timing methods crucial to understanding implosion dynamics. After the war, he founded the renowned MIT Cosmic Ray Group, which evolved into the Center for Space Research. Rossi's group instrumented early space missions that characterized the solar wind, and he championed the first detections that launched x-ray astronomy, demonstrating that the universe is bright in high-energy photons.

The Rossi Fellow carries forward this legacy: rigorous physics, elegant instrumentation by model and algorithm, and science in service to national missions.

For More Information

Learn more about the fellowship and its namesake at the NNSS page: https://nnss.gov/mission/sdrd/bruno-rossi-distinguished-postdoctoral-fellowship-in-science-and-technology/

Qualifications

Eligibility
  • PhD in a STEM discipline (physics, applied physics, nuclear engineering, EE, applied math, CS, or related field) awarded within 3 years of the start date, or all requirements completed by the start date.
  • Demonstrated excellence in at least one of: high-performance scientific computing; accelerator/beam physics; radiation transport; pulsed-power modeling; multiphysics MHD; optimization/UQ; or modern ML/AI for physical systems.
  • Strong written and oral communication skills and the ability to collaborate across disciplines.
  • Demonstrated experience in building successful collaborations across multiple organizations.
  • Effective verbal and written communication skills necessary to collaborate in a team environment
  • and to present and explain technical information to stakeholders.
  • Experience working independently, as well as in a team, with minimal direction in a driven environment
  • Primary duty location is the NNSS' North Las Vegas facility with occasional travel to the NNSS site, LANL, LLNL, and SNL.
  • A 4/10 work schedule (Mon-Thu) is typical and subject to change. Limited hybrid arrangements may be considered depending on program needs and security requirements.
  • Must possess a valid driver's license.

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