Inside Higher Ed
Computational Biologist & Project Manager in Genomics (Biostatistician 2)
Inside Higher Ed, Palo Alto, California, United States, 94306
Computational Biologist & Project Manager in Genomics (Biostatistician 2)
The Engreitz and Kundaje Labs at Stanford University’s Department of Genetics are seeking a Computational Biologist / Project Manager (Biostatistician 2) to help map the regulatory wiring of the human genome and uncover mechanisms of complex diseases.
Lab Overview
DNA regulatory elements harbor thousands of genetic risk variants for common and rare diseases. Our labs combine single‑cell genomics, CRISPR perturbations, and machine learning to create regulatory maps of the human genome.
Project Overview
We will develop computational models to interpret the function of non‑coding variants and genes across many human cell types, leading projects in the MorPhiC and IGVF consortia. The role involves improving predictive models and applying them to large single‑cell and CRISPR datasets collected by MorPhiC and IGVF.
Responsibilities
Apply state‑of‑the‑art machine learning models to large datasets, including single‑cell and Perturb‑seq data
Interpret model performance and results
Develop standards and pipelines to enable analysis across additional datasets
Interface with collaborators at Stanford and external labs to design key methods and data‑analysis products
Track and manage contributions by other lab members to consortium activities
Design and implement generalizable algorithms and tools for analysis of biological data
Evaluate and recommend new emerging technologies, approaches, and problems
Create rigorous visualizations, communications, and presentations of results
Contribute to protocols, publications, and intellectual property
Maintain and organize computational infrastructure and resources
Desired Qualifications
Master’s or Ph.D. in computational biology, genetics, computer science, statistics, math, molecular biology, or related field, or equivalent practical experience
Expertise in statistical methods for high‑throughput sequencing or other biological assays
Experience with data analysis and workflow management
Fluency in Unix and standard bioinformatics tools (Python, R, or equivalent); proficiency in a programming language such as C/C++, Java
Strong knowledge of molecular biology and functional genomics
Ability to mentor and train other lab members in computational biology and statistics
Excellent communication, organization, and time‑management skills
Creative, organized, motivated, team player with passion for science and urgency to find new medicines
Education & Experience (required)
Master’s degree in biostatistics, statistics or related field and at least 3 years of experience
Knowledge, Skills and Abilities (required)
Proficient in at least two of R, SAS, SPSS, or STATA
Skills in descriptive analysis, modeling, and graphical interfaces
Outstanding ability to communicate technical information to technical and non‑technical audiences
Demonstrated excellence in at least one area of expertise (e.g., statistical genetics, informatics, database design, etc.)
Physical Requirements
Frequently perform desk‑based computer tasks, seated work, and light/fine grasping
Occasionally stand, walk, write by hand, lift, carry, push or pull objects up to 10 pounds
Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of his or her job.
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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Lab Overview
DNA regulatory elements harbor thousands of genetic risk variants for common and rare diseases. Our labs combine single‑cell genomics, CRISPR perturbations, and machine learning to create regulatory maps of the human genome.
Project Overview
We will develop computational models to interpret the function of non‑coding variants and genes across many human cell types, leading projects in the MorPhiC and IGVF consortia. The role involves improving predictive models and applying them to large single‑cell and CRISPR datasets collected by MorPhiC and IGVF.
Responsibilities
Apply state‑of‑the‑art machine learning models to large datasets, including single‑cell and Perturb‑seq data
Interpret model performance and results
Develop standards and pipelines to enable analysis across additional datasets
Interface with collaborators at Stanford and external labs to design key methods and data‑analysis products
Track and manage contributions by other lab members to consortium activities
Design and implement generalizable algorithms and tools for analysis of biological data
Evaluate and recommend new emerging technologies, approaches, and problems
Create rigorous visualizations, communications, and presentations of results
Contribute to protocols, publications, and intellectual property
Maintain and organize computational infrastructure and resources
Desired Qualifications
Master’s or Ph.D. in computational biology, genetics, computer science, statistics, math, molecular biology, or related field, or equivalent practical experience
Expertise in statistical methods for high‑throughput sequencing or other biological assays
Experience with data analysis and workflow management
Fluency in Unix and standard bioinformatics tools (Python, R, or equivalent); proficiency in a programming language such as C/C++, Java
Strong knowledge of molecular biology and functional genomics
Ability to mentor and train other lab members in computational biology and statistics
Excellent communication, organization, and time‑management skills
Creative, organized, motivated, team player with passion for science and urgency to find new medicines
Education & Experience (required)
Master’s degree in biostatistics, statistics or related field and at least 3 years of experience
Knowledge, Skills and Abilities (required)
Proficient in at least two of R, SAS, SPSS, or STATA
Skills in descriptive analysis, modeling, and graphical interfaces
Outstanding ability to communicate technical information to technical and non‑technical audiences
Demonstrated excellence in at least one area of expertise (e.g., statistical genetics, informatics, database design, etc.)
Physical Requirements
Frequently perform desk‑based computer tasks, seated work, and light/fine grasping
Occasionally stand, walk, write by hand, lift, carry, push or pull objects up to 10 pounds
Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of his or her job.
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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