Dry-Lab Postdoc — AI/ML in Pediatric Cancer Genomics

St. Jude Children's Research Hospital; Memphis (TN); On-site; USD 60,000 - 75,000; Full time

Job summary

St. Jude Children's Research Hospital in Memphis, TN, seeks a dry-lab Postdoctoral Research Associate to lead computational/AI research identifying therapeutic target pairs for pediatric cancers.

The role combines single-cell/spatial data analysis with wet-lab collaboration in a hybrid wet-dry setting. The candidate will develop AI/agent-based workflows, nominate disease-selective antigens, and contribute to publications while mentoring junior researchers.

Qualifications

• Ph.D. in Computational Biology, Genetics/Genomics, Bioinformatics, Computer Science, Mathematics, Physics, or related field.
• Strong background in quantitative/computational biology and scientific integrity.
• Proficiency in a major programming language used for data analysis (R or Python).

Responsibilities

• Lead independent computational/AI research projects focused on identifying targets for bispecific therapeutic strategies in pediatric cancers.
• Develop AI/agent-based workflows integrating large-scale single-cell, spatial transcriptomic, bulk genomic, functional-genomic, and pharmacologic data.
• Nominate disease-selective cell-surface antigens and combinations based on specificity, co-expression, and rationale.
• Collaborate with wet-lab scientists to design follow-up validation studies.
• Generate publication-quality analyses, figures, and visualizations; contribute to study design and interpretation.
• Lead projects toward publication, draft manuscripts, and respond to reviewer comments.
• Present findings at meetings and conferences; mentor junior lab members.
• Foster a collaborative wet-dry lab environment.

Skills

Computational biology

Python

R

ML/AI

Single-cell analysis

Education

Ph.D. in Computational Biology

Tools

R

Python

ML frameworks

Job description

St. Jude Children's Research Hospital in Memphis, TN, seeks a dry-lab Postdoctoral Research Associate to lead computational/AI research identifying therapeutic target pairs for pediatric cancers.

The role combines single-cell/spatial data analysis with wet-lab collaboration in a hybrid wet-dry setting. The candidate will develop AI/agent-based workflows, nominate disease-selective antigens, and contribute to publications while mentoring junior researchers.