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Bioinformatician- Single-Cell Genomics

University of California San Francisco

Details

Posted: 14-Aug-22

Location: San Francisco, California

Type: Full-time

Salary: Open

Internal Number: 68632BR

The Ye lab at the Department of Medicine, Rheumatology Institute for Human Genetics at UCSF seeks a highly motivated computational biologist with a background in computational biology, computer science, or other related areas. The individual will have a unique opportunity to lead the development of cloud-based analysis pipelines in the AWS environment for population-scale single-cell genomics projects. The incumbent will work closely with an interdisciplinary team of computational biologists, geneticists, and computer scientists to characterize the natural variability in immune response and map the genetic and environmental drivers of that diversity.
Under the supervision of the principal investigator, the qualified candidate will be responsible for developing data analysis pipelines, maintaining and implementing computational methods to the AWS platform, and bringing together diverse multiparameter high-throughput genomic datasets to enable deep data integration and knowledge discovery including but not limited to single-cell transcriptomics (scRNA-seq and single nuclei RNA-seq), immune repertoire sequencing (TCR and BCR), proteomics (scCITE-seq), epigenomics (scATAC-seq), and spatial sequencing. The qualified applicant should be comfortable with the analyses of 10⁴ - 10⁶ cells and have expertise in integrating multimodal data to arrive at biological insights.

Required qualifications:

Bachelor/Master's degree in bioinformatics, biostatics, computational biology, computer science, or related discipline.
Minimum one year of experience in bioinformatics/programming.
Proficiency in C/C++, PERL, Python, R.
Experience with NGS analysis pipelines (e.g. alignment, variant calling, and genome annotation)
Experience analyzing large-scale single-cell datasets (i.e. scRNA-seq, scATAC-seq or CITE-seq)
Experience working on AWS including data storage on S3 and compute on EC2
Strong knowledge of statistical methods including Cox models, logistic regression, linear regression, and elastic net regression.
Strong knowledge of parametric and non-parametric statistics.
Strong background in computational methods development and application.
Experience working in the cloud or on local compute clusters.
Experience with code, data, and analysis management including github and jupyter.
Strong verbal and written communication skills.
Able to work independently and collaboratively as a member of an interdisciplinary team.
Ability to multitask and track projects.

Preferred qualifications:

Knowledge of genomics and immunology is a plus.
Experience managing other large and complex datasets.
Experience with machine learning techniques, such as random forest models, support vector machines, and deep learning.
Familiarity with clinical study design.
Proficiency in high-performance computing language such as C++, Julia, and C.
Experience with collaborative projects with biologists and domain experts.

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About University of California San Francisco

The University of California, San Francisco (UCSF) is a leading university dedicated to promoting health worldwide through advanced biomedical research, graduate-level education in the life sciences and health professions, and high-quality patient care. It is the only UC campus in the 10-campus system dedicated exclusively to the health sciences.

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