Postdoctoral Fellow - Computational Oncology

City of Hope • Monrovia, CA

4d • Onsite

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 Lab is seeking highly motivated applicants for a postdoctoral position in computational oncology, artificial intelligence, and data science. Our research program focuses on developing digital tumor models that integrate clinical and molecular data to predict treatment response, therapeutic resistance, disease progression, recurrence, toxicity, and survival. We work closely with medical oncologists, surgeons, and translational investigators to embed these efforts within ongoing clinical trials at City of Hope, enabling the development and validation of clinically relevant predictive models. The lab also maintains extensive collaborations with experimental and computational scientists across multiple academic, industry, and government partners.
Trainees will have access to unique multimodal datasets derived from prospective clinical trials, large-scale electronic health record (EHR) resources, medical imaging, and multi-omic profiling platforms, including genomic, transcriptomic, proteomic, and circulating biomarker data. The lab provides access to state-of-the-art computational infrastructure, including high-performance computing (HPC) environments, GPU-enabled systems, and cloud-based resources for large-scale data analysis and model development. Using these rich data resources, we develop and apply advanced AI/ML methods to model tumor evolution, identify clinically actionable patient subgroups, and support personalized treatment strategies. Through these efforts, we aim to translate data-driven insights into clinically actionable tools that improve precision oncology and patient outcomes.
More information about the lab can be found here: https://www.nathlab.org

Requirements

• Ph.D. in genetics, cancer biology, computational biology, bioinformatics, computer science, systems biology, or a related field with relevant experience.
• Candidates from quantitative disciplines, including engineering, mathematics, and statistics, are also encouraged to apply if they have experience and interest in 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 analysis and predictive modeling is highly desirable.
• Experience with software development, cloud computing, data engineering, algorithm design, or scalable computational workflows is a strong plus.

Responsibilities

• Develop AI/ML models to predict patient outcomes, treatment response, disease progression, and survival using multimodal clinical and molecular data.
• Build and maintain computational pipelines for large-scale biomedical data analysis.
• Perform analyses in high-performance computing (HPC) and GPU-enabled environments.
• Collaborate with clinicians, computational scientists, and data scientists in a highly interdisciplinary setting.
• Present findings at internal and external collaborative meetings, scientific conferences, and publish in peer-reviewed publications.
• Work with the Principal Investigator to develop a personalized career development plan.

Benefits

• Comprehensive Benefits

What This Job Offers

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