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Postdoctoral Fellow in Computational Biology, AI/ML, and Cancer Systems Biology We are seeking highly motivated postdoctoral fellows in computational biology, cancer systems biology, and artificial intelligence/machine learning to join our research group at UT MD Anderson Cancer Center. The fellows will contribute to the development of a new AI/ML-driven paradigm for precision oncology, integrating computational methodology with large-scale translational and clinical datasets. Projects will span both the development of novel machine-learning and computational approaches and their application to biologically and clinically important problems in cancer.

Our group has assembled extensive collections of single-cell and spatial omics data, multi-omics datasets, functional and pharmacologic data, and clinically annotated patient cohorts across multiple cancer types. Fellows will also have opportunities to work closely with clinical, translational, and experimental collaborators and to participate in the generation of new datasets using cutting-edge spatial imaging and profiling technologies. This environment provides an unusual opportunity to develop computational methods and rapidly evaluate their biological and translational relevance.

Why join our group This position offers access to an exceptionally rich collection of spatial omics, single-cell, multi-omics, and clinically annotated datasets, together with numerous unanswered biological and translational questions. Fellows will have considerable opportunities to lead projects, develop independent research directions, collaborate across disciplines, and generate high-impact publications. The research program is well funded through multiple NIH, CPRIT, and other research awards, providing strong support for ambitious computational and translational projects.

UT MD Anderson Cancer Center is one of the world's leading institutions for cancer research and clinical care and provides an outstanding environment for computational, translational, and interdisciplinary research. Salaries and benefits are highly competitive. Houston is one of the most diverse and dynamic cities in the United States, with excellent neighborhoods and schools, internationally recognized museums and performing arts organizations, outstanding restaurants, and extensive year-round recreational opportunities.

All duties and responsibilities are carried out in compliance with institutional policies, ethical research standards, and applicable federal and state regulations. LEARNING OBJECTIVES The postdoc fellows will work on projects with the objectives: 1. AI/ML and computational modeling for precision combination therapy discovery, including integration of multi-omics, pharmacologic, and clinical data to identify therapeutic vulnerabilities and predict treatment response.

2. AI/ML for single-cell and spatial multi-omics, including development of new approaches to characterize tumor ecosystems, cellular interactions, spatial organization, biomarkers, and therapeutic response. 3.

Major contributions to translational and collaborative projects accross the institution and nation with bioinformatics data analyses and modeling applications ELIGIBILITY REQUIREMENTS Qualifications 1. PhD in a relevant quantitative or biomedical field, such as bioinformatics, computational biology, biophysics, genomics, computer science, statistics, applied mathematics, or a related discipline. 2.

Strong quantitative, computational, and programming skills. 3. Experience with machine learning, statistical modeling, and/or high-dimensional biological data.

4. Knowledge of cancer biology, signaling pathways, tumor biology, or drug-response mechanisms is highly desirable. Ability and enthusiasm to work collaboratively across computational, experimental, and clinical disciplines.

ADDITIONAL APPLICATION INFORMATION Representative publications 1. Luna A, Wang H, Wang L, et al ... Korkut, A

Co-targeting PARP and SHP2 overcomes resistance to apoptosis and induces durable responses in preclinical models of breast cancer. Cancer Research. Under minor revision.

2. Li X, Dowling EK, Yan G, et al... Korkut A, Precision combination therapies based on recurrent oncogenic coalterations

Cancer Discov. 2022;12(6):1542-1559. doi:10.1158/2159-8290.CD-21-0832

3. Li X, Nguyen J, Korkut A. RECOMBINE identifies recurrent composite markers of cell types and states.

Genome Res. 2026;36(6):1221-1237. doi:10.1101/gr.280817.125

4. Johnson A, Shen Y, Zheng X, et al. The actionable transcriptome: a framework for incorporating RNA sequencing into precision oncology.

Nat Rev Clin Oncol. 2026;23(3):213-229. 5.

Vishnoi M, Dereli Z, Yin Z, et al... Korkut A, prognostic matrix gene expression signature defines functional glioblastoma phenotypes and niches. Commun Biol

2026;9:18. doi:10.1038/s42003-025-09245-8. 6

Bozorgui B, Thibault G, Yuan C, et al... Korkut A, CROCHET: a versatile pipeline for automated analysis and visual atlas creation from single-cell spatialomic data. bioRxiv

Published online March 17, 2026. doi:10.64898/2026.03.13.711472. 7

Dereli Z, Bozorgui B, Sanchez M, Hornstein N, Thibault, G, Wang H, Mills GB, Weinstein JN, Overman, MJ, Korkut, A. A spatially resolved single cell proteomic atlas of Small Bowel Adenocarcinoma. Version: 1.

Biorxiv [Preprint]. 2025 February 4. Available from: https://www.biorxiv.org/content/10.1101/2025.02.01.634535v1 DOI: doi.org /10.1101/2025.02.01

634535 8. Franz A, Shen C, Coscia F, et al. Design of combination therapeutics from protein response to drugs in ovarian cancer cells.

eLife. 2025;14:RP106729. doi:10.7554/eLife.106729.2

9. McDaniel JM, Morrissey RL, Chau GP, et al. Multi-omics analysis identifies intrinsic Trp53-driven metastatic breast cancer subtypes.

Sci Adv. In press. 10.

Carapeto F, Bozorgui B, Shroff RT, et al. The immunogenomic landscape of resected intrahepatic cholangiocarcinoma. Hepatology.

2022;75(2):297-308. doi:10.1002/hep.32150. 11

Yan G, Luna A, Wang H, et al... Korkut A, BET inhibition induces vulnerability to MCL1 targeting through upregulation of fatty acid synthesis pathway in breast cancer. Cell Rep

2022;40(11):111304. doi:10.1016/j.celrep.2022.111304. 12

Bozorgui B, Kong EK, Luna A, Korkut A. Mapping the functional interactions at the tumor-immune checkpoint interface. Commun Biol.

2023;6:462. doi:10.1038/s42003-023-04777-3. 13

Dibra D, Xiong S, Moyer SM, et al. Mutant p53 protects triple-negative breast adenocarcinomas from ferroptosis in vivo. Sci Adv.

2024;10(7):eadk1835. doi:10.1126/sciadv.adk1835. POSITION INFORMATION MD Anderson offers full-time postdoc positions with a salary ranging from $64,000 to $76,000

depending on the number of years of postgraduate experience. The University of Texas MD Anderson Cancer Center offers excellent benefits, including medical, dental, paid time off, retirement, tuition benefits, educational opportunities, and individual and team recognition Offsite work arrangements are subject to approval and may be modified or revoked at any time based on business needs, performance considerations, or regulatory requirements. This position may be responsible for maintaining the security and integrity of critical infrastructure, as defined in Section 113.001(2) of the Texas Business and Commerce Code and therefore may require routine reviews and screening

The ability to satisfy and maintain all requirements necessary to ensure the continued security and integrity of such infrastructure is a condition of hire and continued employment. It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state or local laws unless such distinction is required by law. http://www.mdanderson.org/about-us/legal-and-policy/legal-statements/eeo-affirmative-action.html Apply