Research Lead - Stochastic Sequencing Analysis

Research Lead - Stochastic Sequencing Analysis Job Category Fulltime Term Exempt Overtime Eligible  
Exempt Benefits Eligible Benefit Based

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The Ismagilov Lab at the California Institute of Technology is hiring a Research Lead, Stochastic Sequencing Analysis to support an ambitious DARPA BTO project to overcome the ubiquitous noise and scale limitations of using biological sequencing data for artificial intelligence (AI) training and inference.

This intense, fast-paced project runs one year with the goal to transition it to a much larger-scale effort in industry and/or academia.

The Research Lead, Stochastic Sequencing Analysis will work under the supervision of the PI and be integrated into a team of experimental and computational co-workers to develop and implement the necessary computational tools to advance the project.

The successful candidate will have extensive experience developing models and algorithms for analysis of noisy biological data, a deep background in analysis of stochastic processes, and strong bioinformatics expertise in analyzing both long- and short-read sequencing data. The successful candidate will have a strong drive and ambition to develop novel computational methodologies, drive scientific innovation to advance the frontiers of knowledge and technology, and have an outsized impact on multiple fields, including human health and agricultural biosecurity.

• Execute the deliverables of the DARPA project, providing leadership in the computational components of the effort to guide the strategic research direction of computational analyses.
• Design, develop, and implement novel stochastic models and algorithms for overcoming the noise and scale limitations of using biological data for AI training and inference.
• Deploy, maintain, and optimize the state-of-the-art computational tools, including NGS bioinformatic pipelines, that are developed by the lab, its collaborators, and other leaders in the field for this project.
• Collaborate with students/postdocs in the lab and with external collaborators to improve and innovate computational pipelines, enhancing their accuracy, efficiency, and usability.
• Collaborate with students/postdocs and research staff in quality control assessment and troubleshooting of human and microbial sequencing, providing advanced technical guidance and leadership in computational analysis and interpretation.
• Collaborate with and mentor students/postdocs in the analysis and interpretation of next generation sequencing (NGS) datasets from complex clinical samples. Examples of datasets include, Illumina short read shotgun metagenomes, real-time nanopore sequencing, long read shotgun metagenomes, human and bacterial RNA-Seq, 16S/ITS Amplicon sequencing.
• Contribute specialized scientific and technical knowledge to interpret complex results and inform research directions.
• Collaborate with and mentor students/postdocs to design appropriately powered experiments and to perform statistical analyses, including advising on computational study design and analysis strategies.
• Apply specialized, subject-matter expertise to train students/postdocs and research staff on project-relevant computational pipelines and the use of Caltech’s high-performance computing cluster.
• Assist with generating data for grant reports, patents, and publications, including leading or contributing to the preparation of scientific manuscripts and presentations.
• Work with Caltech’s IT to ensure proper data and computing management, helping establish scalable computational infrastructure to support project objectives.

• Ph.D. in bioengineering, computational biology, bioinformatics, biology, molecular biology, or related field, plus 2 years of post-degree industry or academic experience.
• A record of independent and impactful research…