Assistant​/Associate Specialist For the Department of Public Health Sciences-Informatics Division

NATURE AND PURPOSE

The Department of Public Health Sciences at the University of California Davis, School of Medicine is recruiting for a full- or part-time Specialist at the Assistant/Associate rank in Health Informatics.

The position of Specialist has a narrow focus in a specialized area and provides technical expertise in the planning and execution of research projects involving artificial intelligence (AI), natural language processing (NLP), and clinical research informatics. The Specialist applies professional knowledge to support research activities, maintains technical competence in designated areas of specialization, and stays informed of emerging developments in AI-enabled clinical research.

Under the direction of the Principal Investigator (PI), the Specialist collaborates with faculty, staff, and research partners to advance research objectives and contributes to the development of research methods, datasets, analyses, and scholarly products.

Normally, Specialists do not have Principal Investigator (PI) status but may obtain permission by exception and/or collaborate with a PI in preparing research proposals for extramural funding. The Specialist is evaluated for merit and promotion using three basic criteria outlined below.

The incumbent will work under the supervision of Dr. Anderson and be able to work cooperatively and collegially in a diverse environment.

• Apply knowledge of generative AI, NLP, and related technologies to support research initiatives.
• Develop and maintain pilot datasets and research materials used for workflow development, model evaluation, and training activities.
• Organize, validate, and document research datasets, including data provenance and quality assurance procedures.
• Collaborate with research staff and project stakeholders to identify project requirements and implement research workflows.

• Analyze and document user requirements, workflows, and functional specifications for AI-enabled clinical research projects.
• Coordinate with clinical and research stakeholders to gather and synthesize project information.
• Prepare technical documentation, reports, and summaries supporting research objectives and system implementation.
• Identify opportunities to integrate AI technologies with existing clinical research systems and informatics infrastructure.

• Develop, curate, and maintain datasets supporting AI model development and evaluation.
• Perform annotation, labeling, quality control, and curation activities for NLP and machine learning research.
• Conduct evaluations of language models and related AI technologies using established research methodologies.
• Analyze evaluation results and prepare summaries of research findings.
• Contribute to manuscripts, abstracts, presentations, posters, technical reports, and other scholarly products.
• Build and maintain evaluation frameworks and benchmarks to assess model performance, reliability, consistency, and safety in clinical research workflows.
• Document AI methods, data provenance, architectural limitations, and evaluation results to ensure reproducibility and appropriate use.
• Support weekly laboratory meetings and journal clubs through presentation of technical findings and evaluations.
• Participate actively in research meetings, journal clubs, and collaborative scientific discussions.

• Evaluate emerging AI models, platforms, and technologies for applicability to ongoing research projects.
• Design and conduct comparative assessments of prompting strategies, retrieval methods, and model configurations under the direction of the PI.
• Maintain detailed documentation of experimental procedures, model performance, and research outcomes.
• Prepare comparative analyses and recommendations regarding research technologies and methodologies.
• Evaluate LLM architectures, agentic frameworks, APIs, retrieval-augmented generation (RAG) approaches, and prompt engineering strategies for clinical research applications.
• Compare candidate models across accuracy, latency, cost, privacy, and regulatory considerations.

• Conduct comprehensive literature reviews related to artificial intelligence, natural language processing, health informatics, and clinical research.
• Critically evaluate and summarize findings from peer-reviewed publications and technical reports.
• Maintain organized reference libraries and documentation of relevant software tools and research resources.
• Present literature reviews, technical updates, and research progress to project investigators and collaborators/
• Maintain a curated knowledge base of emerging AI methods, benchmarks, software tools, and regulatory guidance relevant to health AI.

• Maintain current knowledge of developments in AI, NLP, clinical research informatics, and related fields.
• Complete and maintain required…