Laboratory Bioinformatics Jobs (NOW HIRING)

A cover letter is required for this role. 

The Kidney Genetics, Genomics, and Advanced Models Laboratory at the UCSF Mission Bay campus is recruiting an individual with expertise in computational biology.
The general responsibilities of this position are as follows:

• Independent analysis of single cell and bulk genomics data including from CRISPR screens, kidney organoid models, and primary cell models. Datasets generated and used by the laboratory include single cell and bulk RNA-seq, single cell and bulk ATAC-sequencing, ChiP-sequencing, and HiC.
• Analysis of biobank scale human genetics data to identify novel genotype-phenotype and gene-environment interactions.
• Figure generation and writing for publications and grant proposals
• Coordination and management of laboratory compute resources

Candidates will be expected to work independently and in a collaborative multidisciplinary team. Opportunities for career development will be provided and encouraged. The candidate will report to Gabriel Loeb, MD, PhD, the Principal Investigator of the Kidney Genetics, Genomics, and Advanced Models Laboratory.

Department Description: 

The Nephrology Division spans multiple campuses with faculty and staff located at the UCSF Health, San Francisco Veterans Affairs Medical Center, and Zuckerberg San Francisco General The Nephrology Division consists of faculty, fellows, and staff whose work is grounded in deep commitment to and respect for patients with kidney disease.

The Nephrology Division has employed and trained leaders in academic nephrology, superb clinical research scientists and basic scientists, and outstanding clinical nephrologists. Our faculty are leading experts in adult nephrology: including acute kidney injury, chronic kidney disease, hypertension, electrolyte disorders, and kidney transplantation.

Our mission continues in this tradition: expanding the frontiers of basic and clinical investigation in nephrology, training the next generation of academic nephrology leaders and providing the highest level of patient care. Our division within and the UCSF School of Medicine overall

Required qualifications: 

• Bachelor's degree in Bioinformatics/ Systems Biology/ Math/ Statistics/ Computer / Computational / Data Science, or Domain Sciences with computer / computational / data specialization or equivalent experience / training.
• 3 or more years of directly relevant programming experience
• Proficiency in at least one programming language used for single-cell analysis (e.g., R or Python), including use of established single-cell analysis frameworks.
• Thorough knowledge of bioinformatics methods, applications programming, web development and data structures.
• Thorough knowledge of bioinformatics programming design, modification and implementation.
• Independently design and execute end-to-end single-cell analysis pipelines.
• Strong project management skills.
• Ability to generate publication-quality figures and clearly communicate analytical results in writing.
• Demonstrated ability to work independently and collaboratively within a multidisciplinary research team.
• Make and defend methodological choices for normalization, integration, and statistical testing
• Partner closely with experimentalists to shape data generation and interpret biological findings.
• Thorough knowledge of modern biology and applicable field of research.
• Communication skills to work with both technical and non-technical personnel in multiple fields of expertise and at various levels in the organization.
• Ability to communicate technical information in a clear and concise manner.
• Ability to interface with management on a regular basis.
• Self motivated, work independently or as part of a team, able to learn quickly, meet deadlines and demonstrate problem solving skills.
• Thorough knowledge of web, application and data security concepts and methods.

Preferred qualifications: 

• PhD degree in Bioinformatics/ Systems Biology/ Math/ Statistics/ Computer / Computational / Data Science, or Domain Sciences with computer / computational / data specialization or equivalent experience. Strong preference for those with experience in advanced single cell sequencing and genomewide association data analyses.Substantial experience with single-cell data integration, batch correction, and multi-modal analysis.
• Experience analyzing perturbation-based single-cell datasets, including CRISPR or pooled screens.
• Experience working with organoid or disease-model single-cell datasets.
• Familiarity with scalable or high-performance computing environments for large single-cell datasets.
• Experience with bulk genomics and human genetics data