We are seeking a developer with a creative and analytical mind to join Sloan Kettering Institutes Single Cell Research Initiative (SCRI). The teams goal is to develop cutting-edge algorithms to interpret the flood of data emerging from single-cell technologies in order to explore questions in tumor heterogeneity, metastasis and the tumor-immune environment. If you would rather apply your superb programming and analytical skills towards a cancer cure than to finance and shopping carts, our dynamic multi-disciplinary team is the place for you. SCRI is directed by computational biologist Dr. Dana Peer, a pioneer with a strong track record of developing new conceptual approaches and widely used tools in the single-cell analysis field. We collect big biological data, primarily from multi-dimensional single-cell technologies such as single-cell RNA sequencing and high-parameter imaging. You will implement algorithms that process, integrate and visualize the multiple data types, allowing 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 can think innovatively and want to make an impact! As a Bioinformatics Software Engineer, you will: - Design and develop algorithms and software to process, normalize, organize, visualize and interpret data from multiple modalities, including from single-cell and imaging technologies
- Design and implement novel machine learning algorithms to integrate genomics data collected from clinical cohorts
- Implement new features, maintain and test existing SCRI code infrastructure
- Evaluate and compare best practices for processing and analyzing different data types
- Provide consultation, guidance and training to research scientists using SCRI tools
Requirements: - Bachelors or Masters degree with 3+ years of programming experience
- Bioinformatics/ Genomics experience and familiarity with common concepts, terminologies and software currently used in the field
- Experience designing large software tools and writing efficient code
- Proficiency in the testing process; ability to debug and modify code
- Analytical, reasoning, mathematical and problem-solving skills to develop algorithms
- Advanced knowledge of algorithms and statistics
- Proficiencyin Python (including building distributablePython modules)
- Experience with design and architecture of relational & NoSQL databases (e.g. MySQL, Redis, MongoDB)
- Familiarity with Jupyter Notebooks
- Proficiency working in a Linux environment
- Proficiency working with Git workflows
Desirable qualifications: - PhD in Math, Physics, or Computer Science is desirable
- Big plus if experienced in
- machine learning
- bioinformatics tools (BWA, STAR, GATK, samtools, IGV, )
- workflow frameworks (e.g. WDL, CWL)
- cloud computing (e.g. AWS, GCP, Azure) and HPC environment (using LSF/SGE/SLURM)
- modern DevOps practices & technologies (e.g. Docker, Jenkins)
- Familiarity with image analysis and microscopy
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