AI/ML Postdoc in Cancer Systems Biology

University of Texas MD Anderson Cancer Center; Houston (TX); On-site; USD 64,000 - 76,000; Full time

Job summary

University of Texas MD Anderson Cancer Center seeks a Postdoctoral Fellow in computational biology, AI/ML, and cancer systems biology to join our research group in Houston.

The fellow will help develop AI/ML-driven paradigms for precision oncology, integrating computational methods with large translational and clinical datasets, and applying novel approaches to cancer biology challenges.

Qualifications

• PhD in a quantitative/biomedical field (e.g., bioinformatics, computational biology, genomics) or related discipline.
• Strong quantitative, computational, and programming skills.
• Experience with ML, statistical modeling, and high-dimensional biological data.
• Knowledge of cancer biology or drug-response mechanisms is desirable.

Responsibilities

• Develop AI/ML approaches for precision oncology using large translational datasets.
• Apply novel computational methods to cancer biology problems.
• Work with single-cell, multi-omics, spatial data across cancer types.
• Collaborate with clinical and experimental teams; generate new datasets.

Skills

Quantitative skills

Programming

Machine learning

Cross-disciplinary collaboration

Education

PhD in a quantitative or biomedical field

Job description

University of Texas MD Anderson Cancer Center seeks a Postdoctoral Fellow in computational biology, AI/ML, and cancer systems biology to join our research group in Houston.

The fellow will help develop AI/ML-driven paradigms for precision oncology, integrating computational methods with large translational and clinical datasets, and applying novel approaches to cancer biology challenges.