Open Postdoctoral position, faculty mentor Thomas Peter Devereaux

Important Info

Faculty Sponsor First name: 
Thomas Peter
Faculty Sponsor Last Name: 
Devereaux
Other Mentor(s) if Applicable: 
Dr. Cheng Peng
Stanford Departments and Centers: 
Stanford Institute for Materials and Energy Sciences (SIMES)
Postdoc Appointment Term: 
Two years
Appointment Start Date: 
July 1, 2026
How to Submit Application Materials: 

Interested candidates are encouraged to contact Dr. Cheng Peng (cpeng18@stanford.edu) to arrange a meeting and discuss research interests and project details.

Does this position pay above the required minimum?: 
No. The expected base pay for this position is the Stanford University required minimum for all postdoctoral scholars appointed through the Office of Postdoctoral Affairs. The FY25 minimum is $76,383.

Postdoctoral Opening within Thomas Devereaux's Group at Stanford University.

Dr. Cheng Peng invites applications for a postdoctoral position supported by a Laboratory Directed Research and Development (LDRD) program.   This appointment spans a 2-year timeframe. The successful candidate will be expected to establish an independent research program while working collaboratively across LCLS, SLAC, and Stanford University. The beginning date is planned as July 1st, 2026.

Specific responsibilities include, but are not limited to, the following:

  • Develop the core tensor network algorithm for full RIXS cross-section simulations.
  • Benchmark simulation results against ED codes on small test clusters.
  • Test computational performance and resolve technical challenges on significantly larger models of selected quantum materials.
  • Work on speeding up Krylov solvers on GPUs. Demonstrate the tensor network simulations using HPC resources for selected case studies.
  • Analyze simulated data and compare directly with RIXS experimental spectra; assist in data interpretation and (if applicable) proposal writing.
  • Develop an open-source code platform.
  • Summarize research outcomes, draft manuscript(s), and prepare future research proposals to secure continued funding.
  • Produce an integration note and prototype plug-in so that LCLS/qRIXS analysis workflows can call the Legion/KDRSolvers-backed RIXS solver, establishing the “not an island” software pathway requested by the directorate.
  • Explore the feasibility of prototyping an LLM-driven interactive GUI that auto-configures key inputs (e.g., Slater parameters), enabling a closed loop from model setup to analysis for accelerated studies of new materials in the planned codebase, enabling support for experiments in a user-friendly way.

SIMES (Stanford Institute for Materials and Energy Sciences) sits at the intersection of Stanford, a world- leading university, and SLAC National Accelerator Laboratory, a U.S. Department of Energy national laboratory. As a joint institute of Stanford and SLAC, SIMES brings a combination of intellectual resources and first-class experimental facilities to bear on the energy and security challenges facing our nation and the world.

Required Qualifications: 

To be successful in this position, you will bring:

A Ph.D. in physics, computational condensed matter physics, or a related discipline, and relevant experience in the following:

  • Expertise in RIXS theoretical modeling and computational analysis of a wide range of quantum materials.
  • Proficiency in code development of tensor networks or DMRG in MPS/MPO language to meet dynamic project demands.
  • Demonstrated expertise in coding within HPC environments, with strong proficiency in reading and adapting large-scale codes developed for parallel computing.
  • Record of excellence in professional achievement, as evidenced by a strong publication record.
  • Demonstrated ability to carry out independent research and work in a collaborative environment.
  • Demonstrated effectiveness in written and oral communication, and the ability to synthesize complex technical and scientific information.
Required Application Materials: 
  • CV

 

Stanford is an equal opportunity employer and all qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by law.