Postdoctoral Fellow - Computational Oncology

City of Hope • Monrovia, CA

9d

About The Position

Join the forefront of groundbreaking research at City of Hope where we're changing lives and making a real difference in the fight against cancer, diabetes, and other life-threatening illnesses. Our dedicated and compassionate faculty and staff are driven by a common mission: Contribute to innovative approaches in predicting, preventing, and curing diseases, shaping the future of medicine through cutting-edge research.
The Nath Laboratory is seeking highly motivated applicants for a postdoctoral position in computational oncology and data science. Our research program aims to advance precision oncology through two interconnected areas:
Understanding the biological mechanisms of cancer progression and therapeutic resistance: We integrate diverse molecular and clinical data modalities, including genomic, transcriptomic, epigenomic, proteomic, metabolomic, and circulating biomarker data derived from patient tissues and liquid biopsies. Our goal is to characterize the molecular processes that drive tumor evolution, treatment resistance, and disease progression across multiple cancer types, including breast cancer, lung cancer, glioblastoma, ovarian cancer, and hematologic malignancies.
Developing predictive models for precision oncology: We leverage large-scale multimodal datasets, including molecular profiling, clinical records, imaging, and longitudinal treatment histories, to develop artificial intelligence and machine learning (AI/ML) models that predict therapeutic response, identify clinically actionable patient subgroups, and support personalized treatment strategies. Through these efforts, we aim to accelerate the translation of molecular and clinical insights into tools that improve patient outcomes.
More information about the lab can be found here: https://www.nathlab.org

Requirements

• Ph.D. in computational biology, bioinformatics, computer science, systems biology, or a related quantitative field. Candidates from other disciplines, including engineering, mathematics, and statistics, are particularly encouraged to apply if they have experience in machine learning, systems modeling, optimization, or analysis of complex biological and clinical data.
• Demonstrated proficiency in programming languages such as Python and/or R, with experience analyzing large-scale molecular, clinical, or biomedical datasets.
• Experience developing or applying machine learning, statistical modeling, or artificial intelligence methods to complex biological, clinical, or engineering problems.
• Excellent written and verbal communication skills, with the ability to work effectively in a highly collaborative and interdisciplinary research environment.

Nice To Haves

• Familiarity with multi-omic data integration, predictive modeling, systems biology, biomedical data science, or related analytical methodologies is highly desirable.
• Experience with software development, cloud computing, data engineering, algorithm design, or scalable computational workflows is a strong plus.

Responsibilities

• Collaborate closely with computational scientists, experimental biologists, engineers, mathematicians, and medical oncologists to design and execute integrative cancer research studies.
• Develop, maintain, and optimize computational pipelines for the integration and analysis of multimodal molecular and clinical datasets, including data generated from patient tissue specimens and liquid biopsies.
• Design and apply state-of-the-art AI/ML methods to uncover mechanisms of disease progression, predict treatment response, and develop clinically actionable precision oncology models.
• Contribute to the development of innovative analytical frameworks for integrating heterogeneous biomedical datasets across molecular, clinical, and population-scale sources.
• Stay current with advances in computational biology, data science, systems biology, biomedical engineering, and AI/ML, and present findings to internal teams, collaborators, and at scientific conferences.
• Work closely with the Principal Investigator to develop a personalized career development plan and pursue opportunities for scientific and professional growth.

Benefits

• Comprehensive Benefits

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree