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This position offers an exciting opportunity to collaborate with renowned medical physics scientists and physicians who are at the forefront of applying artificial intelligence (AI) to advance patient care in Radiation Oncology. The successful candidate will contribute to cutting-edge projects focused on automation and the development of machine learning models for cancer prognostication and treatment response assessment. This role also provides the chance to join the prestigious Cedars-Sinai Health System—an institution nationally recognized for its exceptional infrastructure and leadership in AI-based translational research.

The Project Scientist works independently and in cooperation with the Principal Investigator to make significant and creative contributions to a research or creative project in any academic discipline. The Project Scientist may be an ongoing member of a research team or may be employed for a limited period of time to contribute highlevel skills to a specific research or creative program.

Project Scientists are not required to carry out independent research or to develop an independent research reputation and do not have teaching responsibilities. Ordinarily, the Project Scientist title will carry out research or creative programs as well as administration of day-to-day lab operations with supervision by a member of the Professorial Series.

The successful candidate will play a key role in advancing computational and translational research within the Department of Radiation Oncology. This position involves developing and automating research pipelines to enhance clinical and imaging data analysis workflows that support innovative cancer research.

Primary Duties and Responsibilities

• Develop and implement research pipelines to extract, curate, and analyze patient and imaging data for clinical and translational research in Radiation Oncology.
• Build and maintain scripts and automated workflows to streamline data processing and quantitative image analysis, including the integration of machine learning models.
• Collaborate closely with scientists, physicians, and the broader Radiation Oncology research team to translate clinically relevant questions into computational solutions.
• Contribute to the design and development of research infrastructure to support data-driven investigations and improve overall research productivity.
• Track and evaluate success based on measurable outcomes, such as workflow automation, improved data accessibility, and resulting research outputs/publications.
• May assist in preparation of grant proposals, submissions, publications and presentations but is not responsible for generating grant funds.
• May serve as PI for certain grants as approved by supervising member of the Professorial Series.
• May participate in publications and presentations as author or co-author.
• May develop, adapt and implement new research techniques and protocols.
• Assists in lab experiments.
• Analyzes, interprets, summarizes and compiles data.
• May lead or train Staff Research Associates and Research Fellows.
• Will assist in day-to-day laboratory activities.
• Appointees on an academic trajectory will be expected to commit a portion of their time to developing an independent range of research.

Job Qualifications: 

• Completion of postdoctoral appointment in area of specialization, as applicable. Knowledge of PI’s area of research specialization. Demonstrated technical competency in a variety of research techniques and protocols

Preferred: 

• Strong computational and programming skills, with demonstrated proficiency in Python and C# (C-sharp).
• Minimum of five (5) years of experience working with patient and imaging data in a hospital or clinical research environment.
• Proven experience developing research infrastructure to support data extraction, management, and analysis.
• Excellent collaboration and communication skills, with the ability to work effectively in a multidisciplinary research environment.
• Demonstrated significant, original, and creative contributions to a research or creative program or project Completion of postdoctoral appointment in area of specialization, as applicable.