Research Fellow, Biochemistry & Molecular Biology

Job Summary

To conduct advanced, independent, and collaborative research within the Department of Biochemistry & Molecular Biology, contributing to the design, prototyping, and evaluation of computational and artificial intelligence systems that support biological discovery. The candidate will design, prototype, and evaluate artificial intelligence systems at the interface of biological data analysis and large language models, focusing on developing computational approaches that combine domain‑specific biological knowledge, structured scientific datasets, and modern LLM‑based reasoning or retrieval systems.

• Conduct independent and collaborative research under the direction of the principal investigator.
• Design and carry out experiments and computational analyses.
• Analyze and interpret research data and verify results.
• Prepare manuscripts, technical documentation, and presentations for publication and scientific meetings.
• Maintain accurate research records and documentation.
• Mentor students and junior staff as needed.
• Adhere to institutional research, safety, and compliance policies.
• Perform related duties as required.

• System design: develop architectures for AI systems that integrate biological datasets, scientific literature, experimental metadata, and large language model capabilities, including retrieval‑augmented generation, agentic workflows, structured reasoning pipelines, or domain‑specific interfaces.
• Biological data integration: identify, organize, and prepare relevant biological data sources (genomic, epigenomic, proteomic, imaging, structural biology, literature‑derived) for use in AI workflows.
• LLM‑based workflow development: design and implement LLM‑powered tools for scientific question answering, hypothesis generation, literature analysis, experimental planning, data interpretation, and automated report generation, evaluating model outputs for scientific accuracy, traceability, and usability.
• Prototype implementation: build working prototypes, scripts, notebooks, APIs, or lightweight applications demonstrating the proposed AI systems, with sufficient documentation for review and further development.
• Evaluation and validation: develop practical evaluation criteria for biological and scientific AI systems, including accuracy, reproducibility, citation grounding, failure modes, hallucination risk, and usefulness to researchers, test systems on representative use cases, and summarize results.
• Documentation and recommendations: prepare clear technical documentation describing system architecture, data inputs, model choices, workflows, limitations, and recommended next steps, suitable for internal scientific and technical review.
• Collaboration:
  
  meet periodically with project leadership and relevant scientific or computational collaborators to review progress, refine priorities, and incorporate feedback.

• Technical design documents for AI systems spanning biology and LLMs.
• Prototype software, notebooks, scripts, or application components.
• Curated or structured biological data inputs for AI workflows.
• Evaluation reports describing system performance, limitations, and risks.
• Written recommendations for future development, deployment, or publication.
• Periodic progress summaries.

The work is expected to produce practical designs and early‑stage prototypes for AI systems that support biological research using large language models, with emphasis on scientific rigor, interpretability, reliable grounding in source material, and usability by researchers.

We are seeking a highly motivated Research Fellow to help build artificial intelligence systems at the intersection of biology and large language models within the Department of Biochemistry & Molecular Biology. The role is ideal for someone who enjoys working across genomics, scientific data, and modern AI, and who wants hands‑on involvement in designing, prototyping, and evaluating tools that accelerate biological discovery while upholding scientific rigor and reliable grounding in source material.

Master’s degree in bioinformatics, computational biology, computer science, genomics, biochemistry, molecular biology, or a related field, or equivalent research experience.

UTMB Health strives to provide equal opportunity employment without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, genetic information, disability, veteran status, or any other basis protected by institutional policy or by federal, state or local laws unless such distinction is required by law. As a Federal Contractor, UTMB Health takes affirmative action to hire and advance protected veterans and individuals with disabilities.