Brookhaven National Laboratory is looking to develop new approaches for using machine learning to analyze X-ray data, particularly Resonant Inelastic X-ray Scattering (RIXS), to better understand the electronic structure of quantum materials.
Requirements
- Experience with scientific programming
- Experience developing Python programs
- Experience with machine learning approaches to analyzing data
- Knowledge of high-performance computing, such as parallelization, the use of C++, or interfacing with specialized linear algebra packages
- Ability to analyze complex multi-dimensional datasets
Responsibilities
- Develop methods to co-analyze multiple datasets using machine learning methods
- Apply novel methodologies to quantum materials to better understand their electronic structure
Other
- Requires a PhD in condensed matter physics, materials science, physical chemistry, computational science, or a related field
- Candidates must have received a Ph.D. by the commencement of employment.
- BNL policy requires that after obtaining their PhD, eligible candidates for research associate appointments may not exceed a combined total of 5 years of relevant work experience as a post-doc and/or in an R&D position, excluding time associated with family planning, military service, illness or other life-changing events.
- Must have a REAL-ID or REAL-ID compliant documentation to access Brookhaven National Laboratory
