Join us as we translate today's discoveries into tomorrow's medicine!

The Coleman Lab at Cedars-Sinai focuses on developing artificial intelligence (AI)-based tools to uncover the biological mechanisms underlying complex human diseases. Our research employs multimodal approaches that integrate various types of spatial molecular and imaging data to gain deeper insights into disease processes and improve predictive modeling. We are seeking a research data scientist with expertise in deep learning for biomedical applications to join our lab. This fully funded position focuses on developing novel multimodal methods for spatial omics analysis. There will be a focus on leveraging spatially resolved biological data, including spatial omics, tissue histology, and magnetic resonance imaging (MRI) to drive advancements in precision oncology. The ideal candidate will have experience in computational biology and biomedical image analysis. Experience with training deep learning models using self-supervised learning on large-scale datasets is also preferred.

Are you ready to be a part of breakthrough research?

The Research Data Scientist participates in biomedical research projects using programming, data mining, statistics, machine learning, and visualization techniques to lead the development, evaluation, and/or application of algorithms, methods, and software for data analysis. Responsibilities include querying databases, data processing, data cleaning and quality control, supervised and unsupervised machine learning, parametric and nonparametric statistical methods, deploying production models, and leading the communication of scientific findings via peer-reviewed publications and scientific conferences. Writes clean, performant, reusable code managed on GitHub to perform repeatable analyses and to train and deploy models to multiple environments.

Primary Duties & Responsibilities:

• Leads the development, evaluation, and/or application of computational and statistical methods including artificial intelligence and machine learning algorithms and software for the analysis of biomedical data.
• Leads with the presentation and communication of scientific results through laboratory meetings, scientific conferences, and peer-reviewed publications.
• Creates database-to-deployment pipelines for models using the necessary programming languages (primarily R, Python, SQL, neo4j).
• Creates sustainable data science infrastructure and adheres to data analysis/machine learning best practices.
• Performs data cleaning, quality control, exploratory data analysis to gauge the need for or appropriateness of advanced analytical methods.
• Leads discussions with senior and/or lead research data scientists and principal investigators to identify areas where data science can best be applied to answer biomedical research questions.
• Tests and validates code to ensure robustness of data applications with version control through GitHub.
• Performs all other duties as assigned.

Education:

• Bachelor's degree in Computer Sciences, Machine Learning, Applied Mathematics, Econometrics, Statistics, Engineering, Physics, or related field, required. Master's degree, preferred.

Experience and Skills:

• Two (2) years of professional experience in healthcare or pharmaceutical industries working with biomedical data.
• Two (2) years of experience programming at an intermediate skill level with a high-level programming language such as R or Python. College projects may be acceptable.
• Two (2) years of experience programming at a basic to intermediate proficiency level in SQL.
• Experience in biomedical machine learning is preferred.
• Collaborates to problem solve and make decisions to achieve desired outcomes.
• Cultivates and maintains strong customer relationships and rapport with stakeholders and/or client groups.
• Working knowledge of data privacy and security including best practices for data with personal health identifiers (PHI) covered under HIPAA.
• Strong interpersonal and communication skills including scientific writing. And has full command (verbal and written) of the English language.
• Demonstrates commitment to customer service and an ability to meet the needs and expectations of patients and health care colleagues.
• Demonstrated success working independently, forging relationships, and managing multiple tasks with minimal directions.
• Ability to promote and foster participation/collaboration among individuals and groups.
• Ability to handle multiple demands and/or manage complex and competing priorities.
• Ability to analyze qualitative and quantitative information for research.
• High level of proficiency using Microsoft Windows and other Microsoft Office software: MS Excel, Outlook, Powerpoint Word, etc.
• Must be able to manage competing priorities, while being extremely adaptable and flexible and maintaining a positive work environment.