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Cedars-Sinai Project Scientist - Artificial Intelligence in Medicine (AIM) in Los Angeles, California

If you're passionate about deep and machine learning research and have a strong background in scientific computing and data management, we invite to consider this great opportunity and apply today!

When the work you do every single day has a crucial impact on the lives of others, every effort, every detail, and every second matters. This shared culture of happiness, passion, and dedication pulses through Cedars-Sinai, and it’s just one of the many reasons why we rank as one of the top hospitals in the nation by U.S. News & World Report.

The mission of the Artificial Intelligence in Medicine Program is to use artificial intelligence to solve existing gaps in mechanisms, diagnostics, and therapeutics of major human disease conditions. Our team includes physician-scientists, data scientists, computer scientists, biostatisticians and bioinformaticians focused on high impact cardiovascular clinical research by leveraging cutting edge machine learning techniques.

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 position may be an ongoing member of a research team or may be employed for a limited period of time to contribute high-level skills to a specific research or creative program. This role is 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.


Primary Job Duties and Responsibilities:

  • 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, understands regulations, policies, and protocols to control and maintain accurate records.

  • Analyzes, interprets, summarizes and compiles data for research studies.

  • May lead or train Staff Research Associates and Research Fellows.

  • Will assist in day-to-day laboratory activities.

Department-Specific Responsibilities:

  • May lead and manage data workflows between imaging (PACS) systems, machine learning pipelines, and clinician interfaces through integration with third-party APIs and development of clinician user interfaces.

  • Designs pipelines for data collection, clinical data abstraction, processing data, maintaining record systems, and debugging deep learning training pipelines.

  • Processes clinical data using a range of computer applications and database systems to support cleaning and management of subject or patient data.

  • Analysis of research data using PyTorch, Scipy, and applicable analysis applications and packages.

  • Maintains accuracy, integrity, and security of complex, large computerized records systems.


  • Doctorate degree in Computer Science, Electrical Engineering, Physics, Math, Economics, Statistics, or related field is required.

  • Demonstrated significant, original, and creative contributions to a research or creative program or project.

Experience and Skillset:

  • Completion of postdoctoral appointment in area of specialization, as applicable.

  • Knowledge of PI’s area of research specialization

  • Expertise in deep machine learning, scientific computing, proficiency with Python, R, SQL, OpenCV, Pydicom, SciPy, Tensorflow, and PyTorch.

  • Familiarity in Unix/Linux environments including command line and SSH.

Cedars-Sinai is an EEO employer. Cedars-Sinai does not unlawfully discriminate on the basis of the race, religion, color, national origin, citizenship, ancestry, physical or mental disability, legally protected medical condition (cancer-related or genetic characteristics or any genetic information), marital status, sex, gender, sexual orientation, gender identity, gender expression, pregnancy, age (40 or older), military and/or veteran status or any other basis protected by federal or state law.