Research Scientist at UVA Health

, Virginia, United States -

Full Time

Start Date

Immediate

Expiry Date

25 Jul, 26

Salary

0.0

Posted On

26 Apr, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Large Language Models, Deep Learning, Machine Learning, PyTorch, TensorFlow, Hugging Face, Data Analysis, Transformer Architectures, Fine-tuning, HPC Systems, AI Systems, Problem-solving, Communication, Collaboration

Industry

Hospitals and Health Care

Description

Department Overview The University of Virginia’s Research Computing (RC) team, part of UVA Information Technology Services (ITS), supports cutting-edge research across the institution by providing advanced computational resources and expertise. Within RC, the Data Analytics Center (DAC) enables interdisciplinary collaboration by helping researchers apply modern data science and AI techniques to complex problems. UVA ITS does more than support the UVA community — we empower and move it forward. With every partnership and every solution, we are shaping a culture and ecosystem where learning and discovery thrive. Position Summary The University of Virginia is seeking a Research Scientist with expertise in Large Language Models (LLMs) to join the Data Analytics Center (DAC) within Research Computing. This role will partner directly with researchers across disciplines to apply LLMs and AI techniques to diverse datasets, enabling innovative research outcomes. As a key member of the Research Computing team, you will contribute technical expertise in deep learning and LLMs, support high-impact research initiatives, and help advance UVA’s leadership in data-driven discovery. Responsibilities Collaborate with researchers to understand datasets and analytical requirements Perform data preprocessing and analysis to identify appropriate deep learning and LLM approaches Select, fine-tune, and apply LLMs and AI models to complex research problems Optimize LLM performance on HPC systems, including parallel implementations Manage AI-based research projects to ensure timely delivery and scientific rigor Prepare technical reports, presentations, and research outputs Develop and deliver training sessions and workshops on LLMs for the UVA community Partner with the DAC team to share programming techniques and best practices Minimum Qualifications Education: Advanced degree (Master’s or higher) Experience: At least 2 years of relevant work experience Skills: Proficiency in Python programming Demonstrated expertise in AI systems and machine learning algorithms Strong analytical and problem-solving abilities Excellent written and verbal communication skills Ability to collaborate with researchers across diverse disciplines Strong relationship-building skills with technical and non-technical stakeholders Additional Requirement: U.S. citizenship or permanent residency required due to access to high-security data environments Preferred Qualifications Education: PhD in Computer Science, Electrical Engineering, Data Science, or related field Experience: 3+ years of academic or applied research experience Technical Skills: Deep understanding of transformer architectures (attention, tokenization, embeddings, positional encoding, scaling) Experience with fine-tuning techniques (supervised fine-tuning, instruction tuning, RLHF, domain adaptation) Proficiency with AI frameworks such as PyTorch, TensorFlow, and Hugging Face Experience with LLM evaluation and benchmarking methodologies Familiarity with generative or probabilistic modeling Additional Knowledge: Understanding of LLM risks such as hallucinations and bias, and responsible AI practices Physical Demands This is primarily a sedentary role. The position may require the ability to sit for extended periods and use a computer for prolonged durations. Position Type & Work Location Full-time Located in Charlottesville, VA Flexible work arrangements may be available This position has committed funding through June 2028; continuation is dependent on the availability of funding. About UVA and the Community The University of Virginia is a highly regarded public institution known for its commitment to academic excellence, innovation, and service. Located in Charlottesville, UVA offers a vibrant community with a high quality of life, combining rich history with a dynamic and forward-looking environment. UVA fosters a collaborative culture that values diversity, equity, and inclusion, and is dedicated to supporting employees’ professional growth and work-life balance. Application Timeline Review of applications will begin after the position has been posted for a minimum of five days. Additional Requirements Background check required This position will not sponsor applicants requiring a visa How to Apply Please apply online through Online and search for R0081788 . Complete the application and upload the following required materials: Internal applicants may search and apply for jobs on the UVA Internal Careers website. Cover letter Resume Reference Check Process Reference checks will be conducted via UVA’s standard SkillSurvey process, requiring a minimum of three completed references. Contact For questions about this position, please contact: Bill Crane Senior Talent Acquisition Recruiter University of Virginia Xer5ff@virginia.edu . MINIMUM REQUIREMENTS: Education: Bachelor’s Degree required. Experience: 3+ years relevant experience required. Licensure: None. PHYSICAL DEMANDS: This is primarily a sedentary job involving extensive use of desktop computers. The job does occasionally require traveling some distance to attend meetings, and programs. The University of Virginia is an equal opportunity employer. All interested persons are encouraged to apply, including veterans and individuals with disabilities. Learn more about UVA’s commitment to non-discrimination and equal opportunity employment.

Responsibilities

The Research Scientist will collaborate with researchers to apply Large Language Models and AI techniques to complex datasets. They are responsible for optimizing model performance on HPC systems and delivering training workshops to the university community.