Research Scientist or Postdoctoral Research Associate - School of Data Science

The School of Data Science at the University of Virginia and Professor Yong-Yeol (“YY”) Ahn, Quantitative Foundation Distinguished Professor, are excited to announce two professional research staff positions now open for qualified candidates.

This position offers the opportunity to work on a wide range of data science projects, including-but not limited to-network science, AI and machine learning, computational social science, and the science of science. This position is ineligible for sponsorship.

• Conduct independent and collaborative research in data science.
• Lead and contribute to grant proposals and funded research projects.
• Develop, implement, and publish novel data-driven methods, models, analyses, and tools.
• Collaborate with faculty, students, and external partners on interdisciplinary research.
• Contribute to the intellectual community of the School of Data Science through seminars, workshops, and mentoring.

• Ph.D. in data science, computer science, informatics, statistics, network science, or a related field.
• Strong record of research productivity, demonstrated through publications or equivalent contributions.
• Expertise in one or more of the following: machine learning, network science, natural language processing, computational social science, causal inference, or science of science.
• Strong software engineering and data visualization skills, as well as research communication skills to both technical and non-technical audiences.
• Experience with large-scale data analysis and modern data science tools.
• Good communication skills and enthusiasm for collaborative, interdisciplinary work.

A salary range of $80K - $120K is offered based on experience and education.

This position will primarily work on projects in the science of science and visualization, with flexibility to explore related topics such as large language models (LLMs), interpretable embedding spaces, and network science. This position is eligible for sponsorship.

• Ph.D. in computer science, data science, or a related field.
• Effective written and verbal communication skills.
• Proficient computer programming skills.

• Ability to work independently and collaboratively.
• Excellent analytical and communication skills.
• Experience with large-scale data projects.
• Experience with LLMs.
• Experience with building visualization systems.

Expected salary range between $60k-$70k

• Positions will remain open until they are filled.
• Positions are exempt level and benefit eligible.
• The university will perform background checks on all hires (if required) prior to employment.
• Applicants must currently be authorized to work in the United States. This role will not sponsor for Visas now or in the future.

(visit Health and Other Benefits for additional information)

• UVA Health Plan: the choice between 3 different health plans
• Vision Coverage
• Dental Plan
• Benefit Savings Plans
• Life Insurance
• Disability Benefits
• Paid Time Off: starting with 22 days of time off per year, 12 or more holidays, 8 weeks parental leave

After six months of employment, full-time and part-time (20+ hours) employees in a benefits-eligible position are offered options of:

• Use of up to $5250 per calendar year towards a for-credit degree program or for-credit certificate program
• Use of up to $2000 of the total $5250 noted above per calendar year for professional development including job-related training, conferences, and initial certificate exams.

Please apply through the University of Virginia job board, Careers at UVA , and search for R0077754
. Complete an application online and attach a cover letter detailing your interest and relevant experience as well as your current resume or CV.

Applications that do not contain all required documentation will not receive full consideration.

Internal applicants must apply through their UVA Workday home page. Search “Find Jobs”, enter R0077754
, and attach both a cover letter and current resume or CV.

References will be completed via direct…