Senior Computational Scientist, Cancer Immunotherapy

UT Southwestern Medical Center; Dallas (TX); On-site; USD 140,000 - 190,000; Full time

Job summary

UT Southwestern Medical Center seeks a Computational Research Scientist to lead machine-learning efforts identifying novel therapeutic targets and guiding the engineering of next-generation immunotherapies for cancer. You will build models integrating multi-omic data and work with experimental colleagues to translate findings to the clinic.

The role is senior, high autonomy, with responsibility to set scientific direction, mentor staff, and publish results while collaborating across UT

Qualifications

• Ph.D. in Bioinformatics, Computational Biology, Biomedical Engineering, or related field.
• Master’s degree in computer science, Electrical Engineering, or related field.
• Post-doctoral fellowship preferred.

Responsibilities

• Build predictive models integrating multi-omic and functional data to nominate novel targets in cancer and tumor immunity.
• Apply ML to antigen/neoantigen discovery, protein design, and engineered immune cells optimization.
• Develop methods to interpret high-dimensional and perturbation data, incl. deep learning for sequence, structure, and single-cell readouts.
• Collaborate with wet-lab scientists to design experiments and prioritize candidates for validation.
• Mentor trainees and staff, set analytical standards, shape the program's scientific roadmap.
• Communicate results through high-impact publications and collaborations across UT Southwestern.

Skills

Machine learning

Deep learning

Genomics

Immunology

Single-cell

Python

Bioinformatics

Education

Ph.D. in Bioinformatics/Computational Biology/Biomedical Engineering

Master's in CS/EE or related field

Job description

UT Southwestern Medical Center seeks a Computational Research Scientist to lead machine-learning efforts identifying novel therapeutic targets and guiding the engineering of next-generation immunotherapies for cancer. You will build models integrating multi-omic data and work with experimental colleagues to translate findings to the clinic.

The role is senior, high autonomy, with responsibility to set scientific direction, mentor staff, and publish results while collaborating across UT