Principal Investigator, Dr. Ryan Urbanowicz, is seeking a Postdoctoral Scientist to join the Department of Computational Biomedicine!

The primary focus of the URBS Lab (Unbounded Research in Biomedical Systems) is the development, evaluation and application of machine-learning (ML) and artificial intelligence (AI) tools/methods targeting various biomedical data types and problems. We develop and apply methods that (1) automate and provide rigor to machine-learning analyses, (2) can detect complex patterns of association, (e.g., epistasis and heterogeneity), (3) are interpretable/explainable to promote trust and translational adoption, as well as to identify and address sources of bias, (4) scale to “big data” and (5) flexibly adapt to common data challenges, (i.e., missing values, class imbalance, consideration of covariates). We aim to make ML and AI tools that are applicable to a wide variety of biomedical problems and that are accessible, reliable, reproducible, flexible, user-friendly, computationally efficient and transparent. Our lab holds particular interest in the research of rule-based ML, automated ML, feature selection and evolutionary algorithms. To learn more, please visit: Cedars-Sinai | Urbanowicz Lab

Are you ready to be a part of breakthrough research?

The URBS-lab focuses on the development and application of machine learning, artificial intelligence, and statistical methodologies targeting a variety of domains and data types within biomedical research. Emphasis is placed on developing methods that are interpretable/explainable, scalable to ‘big data’, and capable of detecting complex patterns of association. Current research focuses on automated machine learning, rule-based modeling, feature selection, and evolutionary optimization. Other areas of interest include (but are not limited to) rare-variant analysis, data simulation, data integration, heterogeneous patient subgroup identification, time-series analysis, deep learning, and identifying and correcting for biases. We are a highly collaborative lab with access to EHR, genomic, and other ‘omics’ data in areas of research such as obstructive sleep apnea, congenital heart disease, pancreatic cancer, transplantation donor-recipient matching, and hospital readmission.

Working independently but in close cooperation and in consultation with Dr. Ryan Urbanowicz and other research scientists, the Postdoctoral Scientist will perform routine and complex computational, mathematical, and statistical procedures throughout the training period. As a Postdoctoral Scientist you may develop, adapt, and implement new techniques, algorithms, analysis pipelines, and software, as well as analyze, interpret, summarize, and compile data.

Primary Duties and Responsibilities:

• May assist in the preparation of grant proposals, but is not responsible for generating grant funds.
• May participate in publications and presentations as author or co-author.
• Designs and performs experiments. Will keep appropriate experimental records and documentation and analyze the results with the Principal Investigator.
• Analyzes interpret, summarizes, and compiles data.
• Operates and maintains equipment and instruments.
• May observe MD-patient or MD-human research subject interactions as it pertains directly to research being performed.

Education:

• Doctorate (MD, PhD, VMD, or DDS) in computer science, computational biology, data science, bioinformatics, biomedical informatics, biostatistics, engineering, or a related quantitative field is required.

Experience and Skills:

• Competitive candidates will be proficient in scientific writing having published in more than one of the areas mentioned as well as experience with algorithm development/application.
• Including a cover letter and publication examples (first authorship) are preferred, but not required.
• Independently works on research projects designed in collaboration with one or more mentors within an area of specialization.
• Acquires thorough technical and theoretical knowledge of research projects and objectives during one to five (1-5) year post-doctoral appointment.
• Demonstrated aptitude to perform experimental protocols and procedures, including detailed data collection.
• Knowledge of safety standards and maintenance of specialized equipment.