Postdoctoral Fellowship in Statistics and Machine Learning for Scientific Advancement (NIST/GWU) George Washington University in United States

The George Washington University, in collaboration with the National Institute of Standards and Technology (NIST), is offering a postdoctoral fellowship through the Professional Research Experience Program (PREP). This opportunity is ideal for candidates with a strong background in statistics and machine learning who are eager to apply their expertise to real-world scientific challenges.

The successful candidate will work closely with NIST scientists and engineers to develop advanced metrology solutions. Research projects will span diverse fields such as nanotechnology, forensics, and materials science, with a focus on visualization, estimation, uncertainty quantification, and predictive algorithms. Key responsibilities include developing statistical and machine learning models, performing image processing, and utilizing high-performance computing to analyze large datasets. The role also involves communicating complex statistical concepts to interdisciplinary teams.

Applicants must possess a Ph.D. in Statistics or a related field and demonstrate proficiency in R and Python for statistical computing and machine learning. Strong communication skills are essential, and candidates must be eligible to obtain a U.S. Department of Commerce background check. This position offers a unique chance to contribute to high-impact projects, such as measuring nanoparticles (including nanoplastics and nanomedicines) with high throughput.

Funding is provided through the GWU/NIST PREP program, though specific details regarding stipend and benefits are not disclosed in the announcement. Interested candidates should apply via the provided application link and ensure they meet all eligibility requirements. For more information, applicants may contact Professor David Broniatowski at George Washington University.