Position Responsibilities:
· Lead independent computational/AI research projects focused on identifying and prioritizing candidate targets for emerging bispecific therapeutic strategies in pediatric cancers.
· Develop AI and agent-based workflows integrating large-scale single-cell, spatial transcriptomic, bulk genomic, functional-genomic, and pharmacologic datasets to nominate disease-selective vulnerabilities and target combinations.
· Nominate disease-selective cell-surface antigens and antigen combinations based on malignant-cell specificity, co-expression, spatial localization, normal-tissue expression, targetability, and therapeutic rationale.
· Work closely with wet-lab scientists to design follow-up validation studies and interpret experimental results in the context of large-scale datasets.
· Generate publication-quality analyses, figures, and visualizations, and contribute to study design, data interpretation, and project strategy.
· Lead projects toward publication, including drafting manuscripts, preparing methods and results sections, and responding to reviewer comments.
· Present research findings at lab meetings, institutional seminars, collaborative meetings, and scientific conferences.
· Mentor junior lab members and contribute to a collaborative wet-dry lab environment.