Research Scientist ( AI specialist)

The University of Virginia (UVA) is seeking a Research Scientist with expertise in artificial intelligence (AI) to join the Data Analytics Center (DAC) within Information Technology Services' Research Computing (RC).The DAC and RC support UVA's cutting-edge research by providing computational expertise and infrastructure. As part of the DAC team, you will collaborate with researchers across the university, creating or adapting AI models to support innovative research in an inclusive and diverse environment.

Key Responsibilities:

• Engage in collaborative research projects with faculty, postdoctoral fellows, and graduate students, contributing expertise in the use of AI to advance the scientific goals of the university.
• Develop software programs that use AI algorithms, such as Deep Learning and Large Language Models, on the Research Computing platforms to solve complex research problems.
• Optimize AI algorithms for our high-performance cluster, which may include distributing training across multiple GPUs.
• Manage your efforts on AI-based projects, ensuring timely completion and scientific rigor.

• Evaluate and integrate new AI algorithms and frameworks to improve the accuracy, efficiency, and reproducibility of research outcomes.
• Prepare and present detailed reports, visualizations, and publications that effectively communicate the findings and implications of AI projects.
• Collaborate with other members of the Research Computing team to develop and deliver comprehensive training programs that address the evolving needs of the research community.
• Stay current with the latest developments in AI analysis, and actively participate in professional organizations, conferences, and workshops to enhance knowledge.

Minimum Qualifications:

• Advanced degree (Master's or higher) in computer science, electrical engineering, data science, or a related field with a focus on AI.
• 2+ years of relevant work experience.
• Proficiency in programming languages such as Python, R, or Matlab, with a strong emphasis on AI libraries and frameworks
• Coding skills in popular deep learning frameworks, such as PyTorch and transformers
• Familiarity with high-performance computing environments or cloud-based platforms for large-scale AI model training.
• Strong analytical and problem-solving skills.
• Excellent communication skills (both written and verbal).
• Ability to build collaborative relationships with diverse researchers and team members.
• US citizenship or permanent residency (due to high-security data environments).

Preferred Qualifications:

• PhD in computer science, electrical engineering, data science, or a related field with a focus on AI.
• 4+ years of experience in academic research, including publications and work on externally funded grants.
• Solid understanding of AI applications plus additional knowledge for the following:
  • Running AI and other large models on a high-performance computing cluster, including different types of parallelization across GPUs.
  • Using transformer architecture for audio, vision, multimodal, and text analysis.
  • Implementing LLM algorithms and frameworks, including training models from scratch and fine-tuning models.
  • Employing LLM techniques for improved performance, including prompt engineering, fine-tuning, and retrieval augmented generation.
  • Analyzing model performance metrics other than accuracy (e.g., measures to score a text summary).

Employment Details:

• Full-time position with funding secured through June 2028 (continuation contingent on funding availability).

How to Apply:
To apply, please visit UVA's job board at https://jobs.virginia.edu/us/en/ and search for Job ID: R0068331. Submit the following documents:

• Cover letter

• Resume

Application Deadline: February 14th , 2025

The University of Virginia, including the UVA Health System which represents the UVA Medical Center, Schools of Medicine and Nursing, UVA Physician's Group and the Claude Moore Health Sciences Library, are fundamentally committed to the diversity of our faculty and staff. We believe diversity is excellence expressing itself through every person's perspectives and lived experiences. We are equal opportunity and affirmative action employers. All qualified applicants will receive consideration for employment without regard to age, color, disability, gender identity or expression, marital status, national or ethnic origin, political affiliation, race, religion, sex, pregnancy, sexual orientation, veteran or military status, and family medical or genetic information.