Senior Computational Scientist, Cancer Genomics

University of Texas Southwestern Medical Center; Dallas (TX); On-site; USD 120,000 - 180,000; Full time

Job summary

UT Southwestern Medical Center, Center for Cellular Therapies and Cancer Immunology, seeks a Computational Research Scientist to lead the design of High-Performance Computing infrastructure and develop ML-driven biomedical methods. Collaboration with wet-lab scientists will drive hypothesis generation and validation for novel immunotherapies.

This senior role offers autonomy, mentorship of junior scientists, and a path to shape the scientific roadmap of the program within a dynamic cancer

Qualifications

• PhD or MS in a related field with strong computational biology or ML background.
• Experience leading ML projects and collaborating with wet-lab teams.
• Post-doctoral fellowship preferred.

Responsibilities

• Designs and implements the HPC infrastructure for large, multi-institution projects.
• Leads PoCs for biomedical and clinical science applications with industry collaborators.
• Develops algorithms and workflows for high-dimensional data in biomedical contexts.
• Mentors staff and trainees and helps set analytical standards.
• Communicates results through publications, presentations, and collaborations.

Skills

Computational biology

Machine learning

HPC systems

Programming

Education

Ph.D. in Bioinformatics, Computational Biology, Biomedical Engineering, or related field

Master's degree in Computer Science, Electrical Engineering, or related field

Tools

Compute clusters

Parallel file systems

GPU computing

Job description

UT Southwestern Medical Center, Center for Cellular Therapies and Cancer Immunology, seeks a Computational Research Scientist to lead the design of High-Performance Computing infrastructure and develop ML-driven biomedical methods. Collaboration with wet-lab scientists will drive hypothesis generation and validation for novel immunotherapies.

This senior role offers autonomy, mentorship of junior scientists, and a path to shape the scientific roadmap of the program within a dynamic cancer