Research Scientist

School of Data Sci and Society - 397100

Research Professionals

03/09/2026

Temporary Staff (EHRA NF)

Research Scientist

20074268

N000839

1

40

North Carolina, US

$60,000 - $70,000

06/01/2026

12 months

In 2022, UNC Chapel Hill launched the School of Data Science and Society (SDSS), a new school devoted to data science teaching, research, scholarship, service, and creativity. The SDSS vision is to be a leader in shaping the field of data science through an interdisciplinary and rigorous grounding in theory and methods with a human centric approach to the entire data life cycle.

The mission of SDSS is to empower a diverse community of faculty conducting research in the fundamentals and/or the applications of data science. The school is training undergraduate, graduate, and professional students to be the next generation of data science leaders with the knowledge and skills to thrive in this data-driven world. The SDSS will serve the state, the nation, and the world through premier data science educational programs and innovative research directed to advancing the public good with human-centric and ethical applications.

The core elements of the SDSS include porous borders – leveraging our low-walled collaborative Carolina culture to solve major societal problems. Interdisciplinary research clusters that cross disciplines and school boundaries are a vital element of the school. The SDSS is focused on students and education – the emphasis is not just on data science majors but on all students becoming data literate. The school’s culture has an open and transparent structure, governance, and business model.

The position focuses on developing and applying advanced machine learning techniques to improve full-waveform inversion (FWI) across a range of imaging domains, including geophysics and medical ultrasound. The successful candidate will be responsible for designing data-driven models that enhance the accuracy, robustness, and computational efficiency of FWI workflows. Key duties include integrating deep learning with physics-based modeling, implementing scalable training strategies, and validating methods on both simulated and experimental datasets. The role also involves close collaboration with domain experts in imaging sciences and high-performance computing to advance next-generation inversion methodologies. Additional responsibilities include publishing research findings in top-tier journals and conferences.

Relevant post-Baccalaureate degree required (or foreign degree equivalent); for candidates demonstrating comparable independent research productivity, will accept a relevant Bachelor’s degree (or foreign degree equivalent) and 3 or more years of relevant experience in substitution. May require terminal degree and licensure.

N/A

N/A

Not Applicable.