University of California - San Francisco
San Francisco, CA
JOB DESCRIPTIONAPPLY JOB OVERVIEW
The Ye lab at Department of Medicine, Rheumatology, Institute for Human Genetics, CoLabs and the Baker ImmunoX at UCSF is seeking a highly motivated computational biologist. The individual will have a unique opportunity to work with the Ye lab and two recently established initiatives at UCSF: CoLabs and ImmunoX to lead the development of analysis pipelines for COVID-19 related single-cell genomics projects at the populational scale. The Bioinformatician will work closely with an interdisciplinary team of computational biologists, geneticists, immunologists, and computer scientists to understand the immunopathology of COVID-19, and in a broader view, characterize the natural variability in immune response and map the genetic and environmental drivers of that diversity.
Under the supervision of senior data scientist, the qualified candidate will be responsible for developing data analysis pipelines, implementing state-of-the-art computational methods, 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) and epigenomics (scATAC-seq).
DIVISION OF RHEUMATOLOGY / DEPARTMENT OF MEDICINE
We are a team of experimental and computational biologists with the goal of understanding how genetic differences between individuals create variability in cellular function and ultimately disease susceptibility. This effort builds on the development and application of cutting edge genomic (single cell RNA-seq, ATAC-seq, CITE-seq) and computational technologies (linear mixed models, deep learning). The Ye lab focus on the human immune response as the model system and collaborate extensively with clinicians and immunologists.
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 excellence in patient care. It is the only campus in the 10-campus UC system dedicated exclusively to the health sciences.\\",\\"
Required Qualifications: Bacheloru0027s degree in bioinformatics, biostatistics, computational biology, computer science or related discipline
One to three years of relevant experience
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)
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 with 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 multitasking and tracking projects
NOTE: PHYSICAL/HEALTH SCREENING REQUIRED.
Preferred Qualifications: Master s degree in bioinformatics, biostatistics, computational biology, computer science or related discipline
Knowledge of genomics and immunology
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 a high performance computing language such as C++, Julia and C
Experience with collaborative projects with biologists and domain experts
Equal Employment Opportunity: The University of California San Francisco is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran or disabled status, or genetic information.