Assistant Research Professor - Mathematical Oncology

About City of Hope

City of Hope is an independent biomedical research and treatment organization for cancer, diabetes and other life-threatening diseases.

Founded in 1913, City of Hope is a leader in bone marrow transplantation and immunotherapy such as CAR T cell therapy. City of Hope's translational research and personalized treatment protocols advance care throughout the world. Human synthetic insulin, monoclonal antibodies and numerous breakthrough cancer drugs are based on technology developed at the institution. AccessHope™, a subsidiary launched in 2019 serves employers and their health care partners by providing access to City of Hope's specialized cancer expertise.

A National Cancer Institute-designated comprehensive cancer center and a founding member of the National Comprehensive Cancer Network, City of Hope is ranked among the nation's "Best Hospitals" in cancer by U.S. News & World Report and received Magnet Recognition from the American Nurses Credentialing Center. Its main campus is located near Los Angeles, with additional locations throughout Southern California and in Arizona.

City of Hope's commitment to Diversity, Equity and Inclusion

We believe diversity, equity and inclusion is key in serving our mission to provide compassionate patient care, drive innovative discovery, and advance vital education focused on eliminating cancer and diabetes in all of our communities. Our commitment to Diversity, Equity and Inclusion ensures we bring the full range of skills, perspectives, cultural backgrounds and experiences to our work -- and that our teams align with the people we serve in order to build trust and understanding. We are dedicated to fostering a community that embraces diversity - in ideas, backgrounds and perspectives; this is reflected in our work and represented in our people.

Position Summary

This Assistant Research Professor will perform original research in the Division of Mathematic Oncology and provide service for the Biostatistics and Mathematical Oncology Core (BMOC) Shared Resource. The Assistant Research Professor (ARP) will be responsible for mathematical modeling in a wide range of applications aligned with ongoing research at City of Hope, with a primary focus on cancer and including diabetes and metabolism. The ARP will have familiarity with several mathematical model formalisms, for instance, ordinary and partial differential equations, stochastic models, and agent-based models, with demonstrated expertise in one or more of these areas.

The Assistant Research Professor will be able to integrate in vitro, preclinical, and clinical data with mathematical models to provide insight and predictions into the biological system. The ARP is expected to be engaged with several different research projects simultaneously and will act as a liaison between staff and faculty in the BMOC and the City of Hope research community. The ARP is expected to provide modeling and data analysis in a service capacity through the BMOC as well as a collaborative investigator with the possibility to serve as a co-investigator or multiple-principal investigator on research grants.

The ideal candidate will have formal training in Mathematics, Applied Mathematics, Physics, Computer Science, or Engineering, and demonstrate an ability to learn new techniques and become familiar with new fields quickly. The ideal candidate will have outstanding interpersonal and communication skills in order to facilitate collaborations with interdisciplinary groups of researchers and to communicate complex mathematical concepts and results to a non-expert audience. The ARP must demonstrate proficiency with scientific writing as evidenced with a publication record and will be expected to summarize mathematical modeling results in both oral and written formats. As a non-tenure track position, the candidate is not expected to secure external funding or develop an independent research program or lab. The ARP will report to the Director of the Division of Mathematical Oncology.

Key Responsibilities include:

• Perform original research including, but not limited to, the application of a variety of mathematical modeling techniques to experimental and clinical data.
• Read and analyze relevant literature.
• Maintain expertise on genotype and phenotype relationships for studied genes by analyzing the literature.
• Meet mutually agreed goals.
• Regular and timely attendance of lab meetings.
• Contributing to a positive, collaborative environment within the BMOC and the City of Hope research community.
• Supervision of post-doctoral fellows, staff, technologists, and students as needed.
• Develop and maintain expertise in contemporary mathematical modeling methods.
• Serve as an expert reviewer for scientific manuscripts in the domain of expertise.
• Contribute to and assist with grant applications and manuscripts.
• Perform mathematical modeling and/or quantitative analyses of experimental data produced by lab-bench and clinical oncology investigators at City of Hope
• Implement and/or develop algorithms to analyze data with mathematical models
• Utilize data visualization to explore and communicate complex ideas, including nonlinear dynamics and theoretical concepts as they pertain to mathematical oncology research
• Single out and implement preexisting algorithms for the purpose of biomarker discovery and sample classification
• Analyze and model structured data using advanced mathematical methods and implement algorithms and software needed to perform analyses
• Cluster large amounts of lab bench and/or clinical laboratory generated data and process data
• Perform machine learning, and statistical analysis methods, such as classification, time-series analysis, regression, and hypothesis validation methods.
• Perform explanatory data analyses, generate and test working hypotheses, prepare and analyze historical data and identify patterns
• Author research manuscripts and provide figures and results to support grant applications.
• Assist the Supervisor in identification of new methods, materials, equipment, or other items of supply that appear to warrant evaluation. Participate in experimentation of products and in setup and standardization of new equipment.
• Maintain 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.
• Attend departmental meetings as required and participates in the department continuing education program.
• Follow 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. Practice a high level of integrity and honesty in maintaining confidentiality.
• Perform other related duties as assigned or requested.
• Attend departmental meetings as required and participates in the department continuing education program.

Basic education, experience and skills required for consideration:

• Ph.D. Degree or equivalent experience in Mathematics, Physics, Computational Biology/Bioinformatics, Computer Science or related field of study or related field of science
• Two years of mathematical modeling of biological systems
• 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, Python, MATLAB, Julia
• Experience in a Unix and cluster computing environments

Preferred education experience and skills:

• Strong knowledge of mathematical models in cancer
• Experience with statistical and exploratory data analysis techniques
• Experience with analyzing high throughput genomic data is beneficial

Additional Information:

• As a condition of employment, City of Hope requires staff to comply with all state and federal vaccination mandates.

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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