Research Associate, Postdoc, and Research Faculty positions – Mathematical Oncology
- Duarte, CA
Thank you for your interest. Please note, the purpose of this posting is to recruit for on-going and future positions.
About City of Hope
City of Hope, an innovative biomedical research, treatment and educational institution with over 6,000 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.
The Beckman Research Institute at City of Hope is looking for research talent of all levels to work in the Division of Mathematical Oncology due to multiple NIH/NCI grants that have been awarded recently. Research areas include but are not limited to the following:
- Information flow and state transitions at the system and multi-dimensional scales in leukemia progression.
- Exploring the preclinical relevance of therapeutic radio labeled daratumamab (anti-CD38) in combination with anti-CS1 CAR T cells as a novel combinatorial treatment for multiple myeloma
- Experimental-Computational Synthesis of Altered Immune Signaling in Breast Cancer
- Development and validation of a computational prediction model for exogenous neural stem cell migration to sites of brain tumors
- We are currently accepting applications for Research Associates, Postdoctoral Fellows, Staff Scientists and Assistant Research Professor Faculty roles.
Established in 2015, the Division of Mathematical Oncology seeks to translate mathematics, physics and evolution-based research to clinical care. The Division is committed to both developing and applying novel technics of mathematics and physics to translational problems in oncology. To this end, the candidate should be dedicated to multidisciplinary research and demonstrate a track record of publications involving collaborative research in mathematics, physics, engineering, oncology or a closely related field.
Responsibilities vary depending on the specific job position. All positions require a demonstrated ability to communicate scientific findings and mathematical concepts to both technical and lay audiences, both in written form and verbally. Candidates must have the ability to perform basic scientific computing, in the form of scripting or programming in one or more languages. The candidate will be expected to present research findings during regular group meetings, and depending on the position, to larger audiences at the institution and external audiences. All candidates must be comfortable with independent learning and demonstrate an ability to identify algorithms or computational methods required to perform analysis and solve mathematical equations such as ordinary and partial differential equations. All candidates are expected to work well in interdisciplinary teams composed of biologists, clinicians, and computational researchers.
Basic education, experience and skills required for consideration:
- Research Associates – Must have a Bachelor’s Degree, Master’s Preferred in mathematics, physics, engineering, computer science, or a related field.
- Postdoc, Staff Scientist, and Assistant Research Professor Faculty positions: - Must have a Ph.D. in mathematics, physics, engineering, computer science, or a related field.
- Demonstrated ability to analyze and model structured data using advanced mathematical methods and implement algorithms and software needed to perform analyses
- 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
- Experience with analyzing high throughput data such as transcriptomic, proteomic, and/or genomic data Experience with medical imaging (MRI, PET, etc.) and/or image processing
- Experience with information theory and Boolean networks
- Experience and familiarity with contemporary bioinformatics methods a strong plus
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