Research Scientist

UVA Health
Hybrid

About The Position

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. 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.

Requirements

  • Advanced degree (Master’s or higher)
  • At least 2 years of relevant work experience
  • 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
  • U.S. citizenship or permanent residency required due to access to high-security data environments
  • Bachelor’s Degree required.
  • 3+ years relevant experience required.

Nice To Haves

  • PhD in Computer Science, Electrical Engineering, Data Science, or related field
  • 3+ years of academic or applied research experience
  • 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
  • Understanding of LLM risks such as hallucinations and bias, and responsible AI practices

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
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