Computational Biologist I

UT Southwestern Medical Center; Dallas (TX); On-site; USD 90,000 - 130,000; Full time

Job summary

UT Southwestern Medical Center is seeking a motivated bioinformatics staff scientist to support scientific research in a high-complexity computing environment. The role involves applying software, computational methods, and data analysis to biological datasets, and working under the direction of a Principal Investigator to identify suitable approaches.

Ideal candidates will develop analytical pipelines for diverse multi-omic data, translate biological questions into computational insights, and

Responsibilities

• Perform professional work in support of scientific research using software, software development, networking, and/or hardware in a complex computing environment.
• Collaborate with Principal Investigator to determine suitable computational methods and tools to analyze large-scale biological data sets; prepare reports for presentation or publication.
• Develop and refine analytical pipelines for multi-omic datasets and translate biological questions into computational insights.

Job description

With over 75 years of excellence in Dallas-Fort Worth, Texas, UT Southwestern is committed to excellence, innovation, teamwork, and compassion. As a world-renowned medical and research center, we strive to provide the best possible care, resources, and benefits for our valued employees. Ranked as the number 1 hospital in Dallas-Fort Worth according to U.S. News & World Report, we invest in you with opportunities for career growth and development to align with your future goals. Our highly competitive benefits package offers healthcare, PTO and paid holidays, on-site childcare, wage, merit increases and so much more. We invite you to be a part of the UT Southwestern team where you'll discover a culture of teamwork, professionalism, and a rewarding career!

With over 75 years of excellence in Dallas-Fort Worth, Texas, UT Southwestern is committed to excellence, innovation, teamwork, and compassion. As a world-renowned medical and research center, we strive to provide the best possible care, resources, and benefits for our valued employees. Ranked as the number 1 hospital in Dallas-Fort Worth according to U.S. News & World Report, we invest in you with opportunities for career growth and development to align with your future goals. Our highly competitive benefits package offers healthcare, PTO and paid holidays, on-site childcare, wage, merit increases and so much more. We invite you to be a part of the UT Southwestern team where you'll discover a culture of teamwork, professionalism, and a rewarding career!

Job Summary

Perform professional work in support of scientific research using technical knowledge of software, software development, networking, and/or hardware in a complex computing environment. Subject matter expert in multiple areas of computing technology, and specific knowledge of molecular biology and genetics. Works collaboratively with Principal Investigator ("PI") to determine the most suitable computational methods and tools to analyze large-scale biological data sets. Prepare reports for presentation or publication. Responsible for assisting PI in meeting the system needs for multiple research projects and/or labs.

We are seeking a motivated bioinformatics staff scientist with interests in computational analysis of complex biological data. The successful candidate will work with diverse multi-omic datasets, develop and refine analytical pipelines, and help translate biological questions into computationally driven insights. This position offers an excellent opportunity to strengthen in-demand bioinformatics and data science skills, work in a collaborative environment with both computational and experimental researchers, and contribute to impactful publications and discoveries that support future careers in academia, industry, or biotech.

Xu lab pioneers the application of artificial intelligence (AI) -particularly foundation models and LLMs-to drive biological and medical discovery, with a focus on interpretable and generalizable AI frameworks that extend foundation models into genomics, epigenomics, and precision medicine. For example, his team developed an AI-based approach to identify cardiovascular disease genes and validated these findings experimentally in a novel mouse model and preclinical studies, leading to publication in Nature in 2020. More recently, his team developed an LLM-based method that enabled the discovery and experimental validation of a new transcriptional biosensor, published in Science in 2026. His lab has also published multiple LLM algorithms in biology and medical applications, including DEEP-