
Post-Doc Research Associate
University of North Carolina- Chapel Hill
NC-Chapel-Hill, NCResearchSeen 1 day agoSeen in employer's feed 1 day ago
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Job overview
The Department of Physics and Astronomy at UNC‑Chapel Hill seeks a postdoctoral researcher in theoretical nuclear and high‑energy physics, focusing on lattice QCD calculations of hadron structure and developing algorithms and software for large‑scale simulations on DOE leadership‑class computing facilities.
Skills & qualifications
Skills
Full job description
Vacancy ID: PDS004975
Position Summary/Description:
The Department of Physics and Astronomy at the University of North Carolina at Chapel Hill invites applications for a postdoctoral research position in theoretical nuclear and high-energy physics, with emphasis on lattice QCD . The successful candidate will work with Prof. Kostas Orginos on first-principles calculations of hadron structure, including parton distribution functions, generalized parton distributions, and related quantities obtained from non-local matrix elements, as well as on the development of algorithms and software for large-scale lattice QCD simulations on DOE leadership-class computing facilities. Candidates with expertise in related areas, such as lattice field theory algorithms, machine-learning methods for lattice field theory, hadron spectroscopy, or hadron-structure phenomenology, are encouraged to apply. The postdoc will conduct independent and collaborative research, publish in peer-reviewed journals, present results at conferences and workshops, participate in the activities of the HadStruc collaboration and the broader USQCD community, and may help mentor graduate students. The initial appointment is for two years, with renewal for a third year contingent on satisfactory performance and availability of funds.
Education and Experience:
Experience with lattice calculations of hadron structure: PDFs, GPDs, TMDs, form factors, or matrix elements of non-local operators, including perturbative matching.
Experience with lattice QCD software frameworks (e.g., Chroma, QUDA , Grid) and GPU computing.
Experience with statistical analysis of large Monte Carlo datasets, including inverse-problem and Bayesian methods.
Experience using DOE computing allocations ( NERSC , OLCF , ALCF ).
A record of productive collaboration in multi-institutional projects.
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