We are seeking an individual with a creative and analytical mind to join Sloan Kettering Institute’s Single-cell Analytics and Innovation Lab (SAIL). The SAIL team accelerates biomedical discovery through the application of state-of-the-art algorithms to single-cell genomics datasets collected from patients, advanced mouse and organoid models of cancer, and developmental systems. The individual will implement and improve computational pipelines and methods that can be applied to cutting-edge data being generated at SAIL. These data are used to explore diverse questions, including the subjects of tumor heterogeneity, drug resistance, tumor stem cells, mechanisms of immunotherapy, the emergence of metastasis and the tumor-immune environment. SAIL bioinformatics is embedded in the group of Dr. Dana Pe’er, a leader in single-cell data analysis, providing guidance and a highly stimulating intellectual environment for analytical methods development.
You should have a background in statistics, machine learning or computer science; genomics experience is strongly preferred, and you should be excited to learn how to adapt, develop and apply sophisticated algorithms to big biological data at one of the top cancer research institutes in the world. Your implementation of processing and visualization algorithms will allow data scientists, biologists and clinicians to interact with and interpret the data. A key focus is the single-cell profiling of patient samples, with the goal of improving immunotherapy and precision medicine. Join us if you are eager to learn and want to make an impact!
- Implement, apply, and evaluate methods to process, normalize, organize and visualize single-cell sequencing data
- Help to improve software pipelines and computational infrastructure at SAIL
- Prepare Python notebooks for interactive engagement with the data
- Provide initial analysis and biological interpretation of data
- Closely collaborate with research scientists, providing consultation, guidance and training on SAIL tools
- Minimum of Bachelor’s with core biology and computer science courses, or equivalent experience
- Analytical, reasoning, statistical, mathematical and problem-solving skills
- Excellent ability to communicate with biologists
- Familiarity with high-throughput sequencing data
- Prefer experience with processing genomic data from sequencing technologies
- Knowledge of Python or R (preferably Python)
To apply, please visit the MSK Career Portal.