Postdoc or staff positions of computational biologists at UT Southwestern Medical Center

Background

Multiple openings are available for highly motivated and creative individuals to join the Xu Lab at UT Southwestern Medical Center. Successful candidates will analyze genomic, epigenomic, and transcriptomic data from patient cohorts and develop and maintain computational pipelines. This position offers an excellent opportunity to rapidly build highly sought-after bioinformatics skills, collaborate closely with wet-lab scientists to experimentally validate computational predictions, and publish high-impact manuscripts in bioinformatics and AI that support career advancement in industry or academia.

Dr. Lin Xu has developed multiple deep learning models and statistical algorithms to identify novel disease genes and therapeutic targets [e.g., Huang et al. Nature (2020), Lu et al. Nature Machine Intelligence (2022), Chai et al. Nature Medicine (2022), Takahiko et al. Science Translational Medicine (2022) (Cover Story), Shi et al. Cancer Cell (2022), Lebek et al. Science (2023), Xu et al. Nature Communications (2023), Zhu et al. Cancer Cell (2023), Zhang et al. Journal of Clinical Investigation (2023), He et al. Nature Communications (2023), Yu et al. Nature Communications (2023), Santos et al. Nature Communications (2023), Li et al. Nature Communications (2023), Wei et al. Cell (2023), Hernandez et al. PNAS (2024), Hu L et al. Mol Cell (2024), Eglenen-Polat et al. Nature Communications (2024), Lin CC et al. Nature Communications (2024), Xu L. et al. Nature Communications (2024), Venkateswaran N. et al. Nature Communications (2024), Chen S. et al. Nature Communications (2025), Liao C, Nature Communications (2025), Yang X. et al. Nature Immunology (2025), Lu ZY. et al. Nature Communications (2025), Zhou Y. et al. Nature Communications (2025), Adachi Y et al. J Clin Invest. (2025), Napolitano F, et al. J Clin Invest. (2025), Bann et al. Circulation (2025), Ding et al. Circulation (2025), Caravia XM, et al. Proc. Natl. Acad. Sci. (2025), Guan P, et al. Proc. Natl. Acad. Sci. (2025), Engreitz JM, et al. Nature (2025), Li H et al., Science (2026)]. Since 2022, his lab’s research has been published in a series of high-impact journals, including Nature, Science, Cell, Nature Medicine, Cancer Cell, eLife, PNAS, Nature Machine Intelligence, Nature Immunology, Nature Metabolism, Nature Communications, Science Translational Medicine, Science Advances, Molecular Cell, Genes & Development, Cell Reports, Journal of Clinical Investigation, Circulation, Circulation Research, and Developmental Cell.

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

Building on these publications in bioinformatics and AI fields, the Xu Lab has received support from multiple funding sources, including the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Cancer Institute (NCI), National Heart, Lung, and Blood Institute (NHLBI), National Human Genome Research Institute (NHGRI), National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), Cancer Prevention and Research Institute of Texas (CPRIT), U.S. Department of Defense (DoD), Hyundai Foundation, Children’s Cancer Fund, Sam Day Foundation, Rally Foundation, and Andrew McDonough B+ Foundation. Therefore, these new openings will be supported on a multi-year basis.

Position Title

Postdoctoral Researcher or Staff Data Scientist

(Title will be determined based on the candidate’s qualifications and career stage.)

Position Qualifications

1) Ability to lead first-author manuscripts using large-scale single-cell or spatial omics data from patients already available in the Xu lab.

2) Experience with NGS data analysis and development of customized sequencing-analysis pipelines is strongly preferred.

3) Experience with Linux environments and command-line tools is required.

4) Doctoral degree in bioinformatics, genetics/genomics, statistics, biostatistics, computer science, systems biology, or a related field.

5) Excellent spoken and written English communication skills.

Xu Lab website

https://qbrc.swmed.edu/labs/xulab/about.php

Contact

Candidates should email a CV/resume directly to:

Lin Xu, Ph.D. (Lin.Xu@UTSouthwestern.edu)

Application Deadline

Open until filled; applications will be reviewed on a rolling basis.