Bruno Rossi Distinguished Postdoctoral Fellowship (Senior Scientist)

Mission Support and Test Services, LLC (MSTS) manages and operates the Nevada National Security Site (NNSS) for the U.S. National Nuclear Security Administration (NNSA). Our MISSION is to help ensure the security of the United States and its allies by providing high-hazard experimentation and incident response capabilities through operations, engineering, education, field, and integration services and by acting as environmental stewards to the Site’s Cold War legacy. Our VISION is to be the user site of choice for large-scale, high-hazard, national security experimentation, with premier facilities and capabilities below ground, on the ground, and in the air. (See NNSS.gov for our unique capabilities.) Our 2,750+ professional, craft, and support employees are called upon to innovate, collaborate, and deliver on some of the more difficult nuclear security challenges facing the world today.

• MSTS offers our full-time employees highly competitive salaries and benefits packages including medical, dental, and vision; both a pension and a 401k; paid time off and 96 hours of paid holidays; relocation (if located more than 75 miles from work location); tuition assistance and reimbursement; and more.
• MSTS is a limited liability company consisting of Honeywell International Inc. (Honeywell), Jacobs Engineering Group Inc. (Jacobs), and HII Nuclear Inc.

Responsibilities

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:

• Curriculum Vitae (with education, publications, software contributions, and up to three references to key codes or datasets).
• Research Statement (≤ 3 pages): proposed 2–3 projects aligned to Focus Areas; include methods, anticipated milestones, and potential collaborators.
• Selected Publications or preprints demonstrating relevant expertise.
• 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: April 6, 2026, 11:59 PM Pacific Time
• Interviews: May–June 2026
• Decisions: July 2026
• Start date: October 1, 2026 (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).