Stanford University (US)
Computational Biologist & Project Manager in Genomics (Biostatistician 2)
Stanford University (US), Stanford, California, United States, 94305
The Engreitz and Kundaje Labs are seeking a Computational Biologist / Project Manager (Biostatistician 2) to join the Department of Genetics to map the regulatory wiring of the human genome to discover genetic mechanisms of disease.
Lab overview: DNA regulatory elements in the human genome, which harbor thousands of genetic risk variants for common and rare diseases and could reveal targets for therapeutics that aim to precisely tune cellular functions - if only we could map the complex regulatory wiring that connects 2 million regulatory elements with 21,000 genes in thousands of cell types in the human body. The Engreitz and Kundaje Labs have developed new experimental approaches and computational methods that could enable mapping this regulatory wiring at massive scale.
Project overview: We aim to develop and apply computational models to interpret the function of any noncoding variant or protein-coding gene in the human genome, across many human cell types in the body. Toward this goal, we are leading highly collaborative projects in two NIH-funded Consortia: MorPhiC and IGVF. This position will involve improving predictive models of variants, enhancers, and genes and applying them to large single-cell and CRISPR datasets generated by MorPhiC and IGVF to create a comprehensive catalog of the regulatory wiring of the genome.
Responsibilities
Apply state-of-the-art machine learning models to large datasets, including single-cell and Perturb-seq datasets Interpret model performance and results Develop standards and pipelines to enable expansion of such analyses across additional datasets Interface with collaborators at Stanford and in collaborating labs around the country to design and produce key methods and data analysis products Track and manage contributions by other members of our labs to consortium activities Design and implement generalizable algorithms and tools for analysis of biological data, including high-throughput functional genomics assays Evaluate and recommend new emerging technologies, approaches, and problems Create scientifically rigorous visualizations, communications, and presentations of results Contribute to generation of protocols, publications, and intellectual property Maintain and organize computational infrastructure and resources Qualifications
Required: M.S. or Ph.D. in computational biology, genetics, computer science, statistics, math, molecular biology, or related field, or equivalent practical experience. Demonstrated expertise in statistical methods in data analysis, preferably with applications to high-throughput sequencing or other biological assays Experience with data analysis and management, workflow management Fluency in Unix, standard bioinformatics tools (Python, R, or equivalent), and a programming language (C/C++, Java) Strong knowledge of molecular biology and functional genomics Mentor and train other lab members in computational biology and statistics Excellent communication, organization, and time management skills Creative, organized, motivated, team player A passion for science and sense of urgency to find new medicines to benefit patients Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.
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Apply state-of-the-art machine learning models to large datasets, including single-cell and Perturb-seq datasets Interpret model performance and results Develop standards and pipelines to enable expansion of such analyses across additional datasets Interface with collaborators at Stanford and in collaborating labs around the country to design and produce key methods and data analysis products Track and manage contributions by other members of our labs to consortium activities Design and implement generalizable algorithms and tools for analysis of biological data, including high-throughput functional genomics assays Evaluate and recommend new emerging technologies, approaches, and problems Create scientifically rigorous visualizations, communications, and presentations of results Contribute to generation of protocols, publications, and intellectual property Maintain and organize computational infrastructure and resources Qualifications
Required: M.S. or Ph.D. in computational biology, genetics, computer science, statistics, math, molecular biology, or related field, or equivalent practical experience. Demonstrated expertise in statistical methods in data analysis, preferably with applications to high-throughput sequencing or other biological assays Experience with data analysis and management, workflow management Fluency in Unix, standard bioinformatics tools (Python, R, or equivalent), and a programming language (C/C++, Java) Strong knowledge of molecular biology and functional genomics Mentor and train other lab members in computational biology and statistics Excellent communication, organization, and time management skills Creative, organized, motivated, team player A passion for science and sense of urgency to find new medicines to benefit patients Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.
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