Assistant Research Professor

10000439 Requisition #
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About City of Hope

City of Hope, an innovative biomedical research, treatment and educational institution with over 6000 employees, is dedicated to the prevention and cure of cancer and other life-threatening diseases and guided by a compassionate, patient-centered philosophy.

Founded in 1913 and headquartered in Duarte, California, City of Hope is a remarkable non-profit institution, where compassion and advanced care go hand-in-hand with excellence in clinical and scientific research.  City of Hope is a National Cancer Institute designated Comprehensive Cancer Center and a founding member of the National Comprehensive Cancer Network, an alliance of the nation’s leading cancer centers that develops and institutes standards of care for cancer treatment.

Position Summary

Performs original research in Quantitative Systems Pharmacology and Mathematic Oncology. The Assistant Research Professor will be responsible for QSP modeling, which combines computational modeling and experimental data to examine the relationships between drug(s), the biological system, and the disease process. The Assistant Research Professor will integrate available in vitro, preclinical (animal), and clinical (patient) data representing existing knowledge to subsequently directly inform new discoveries of existing therapies and attributes of disease progression.  The QSP modeling will initially focus on predicting interindividual variability in pharmacokinetics and drug-response (pharmacodynamics) in hematologic malignancy and hematopoietic cell transplant (HCT) patients.   The position will be jointly based in the highly collaborative laboratories of Dr. Jeannine McCune and Dr. Russ Rockne. 

Key Responsibilities include:

  1. Research:  Quantitative systems pharmacology (QSP) and mathematic oncology.  Perform original research including, but not limited to, the role of QSP modeling to predict interindividual variability in pharmacokinetics and drug-response (pharmacodynamics) in hematologic malignancy and hematopoietic cell transplant (HCT) patients.
    1. Read and analyze the relevant literature.
    2. Maintain expertise on genotype and phenotype relationships for studied genes by analyzing the literature.
    3. Meet mutually agreed goals.
    4. Regular and timely attendance of lab meetings.
    5. Contributing to a positive lab environment.
    6. Supervision of post-doctoral fellows and technologists as relevant for research activities only.
    7. Develop and maintain world expertise in pharmacokinetic/dynamic and QSP modeling in hematologic malignancy patients.
    8. Write two original scientific manuscripts.
    9. Review scientific and educational manuscripts.
    10. Contribute and assist in grant applications
  2. Perform mathematical modeling and/or quantitative analyses of experimental data produced by lab-bench and clinical oncology collaborators.
  3. Implement and/or develop algorithms to analyze metabolomic data with pharmacokinetic models.
  4. Utilize data visualization to explore and communicate complex ideas, including nonlinear dynamics and theoretical concepts as they pertain to pharmaco-kinetic metabolomic research.
  5. Single out and implement preexisting algorithms for the purpose of biomarker discovery and sample classification.
  6. Analyze and model structured data using advanced mathematical methods and implement algorithms and software needed to perform analyses.
  7. Cluster large amounts of lab bench and/or clinical laboratory generated data and process data.
  8. Perform machine learning, and statistical analysis methods, such as classification, time-series analysis, regression, and hypothesis validation methods.
  9. Perform explanatory data analyses, generate and test working hypotheses, prepare and analyze historical data and identify patterns
  10. Author research manuscripts and provide figures and results to support grant applications.
  11. Assists the Supervisor in identification of new methods, materials, equipment or other items of supply that appear to warrant evaluation.  Participates in experimentation of products and in setup and standardization of new equipment.
  12. Maintains professional growth and development through seminars, workshops, and professional affiliations to maintain certification/licensure, and/or keep abreast of latest trends in field of expertise. 
  13. Attends departmental meetings as required and participates in the department continuing education program. 

Follows established City of Hope and department policies, procedures, objectives, performance improvement, attendance, safety, environmental, and infection control guidelines, including adherence to the workplace Code of Conduct and Compliance Plan.  Practices a high level of integrity and honesty in maintaining confidentiality. 


Performs other related duties as assigned or requested.

Basic education, experience and skills required for consideration:


Minimum Education

  • Ph.D. Degree or equivalent experience in Pharmaceutical Sciences, Physics, Biochemistry, Computational Biology/Bioinformatics, Mathematics, Computer Science or related field of studyor related field of science

Minimum Experience

  • Two years of mathematic modeling of biological systems

Preferred education experience and skills:

  • Strong knowledge of cancer biology and pharmacokinetic or ordinary differential equation models
  • Experience with statistical and exploratory data analysis techniques
  • Experience with analyzing high throughput data such as proteomic, metabolomic and other forms of genomic data is beneficial



  • Knowledge of biological data sources (e.g. NCBI, Ensembl, Cosmic, TCGA, etc.)
  • Proficiency with at least one of the following high-level programming languages:  R/S-PLUS, MATLAB, SAS
  • Programming experience in Java, Python and experience with databases and SQL highly desirable
  • Experience in a Unix and cluster computing environments

City of Hope is committed to creating a diverse environment and is proud to be an equal opportunity employer.  All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, sex, sexual orientation, gender identity, age, status as a protected veteran, or status as a qualified individual with disability.

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