Associate or Full Specialist – Diaz lab Full-time

Associate or Full Specialist – Diaz Lab

Specialist Series (Associate or Full Specialist), full-time, one-year appointment, Department of Neurological Surgery/Diaz Lab. The incumbent will support computational and translational brain-tumor research by developing, documenting, and applying reproducible bioinformatics workflows for bulk and single-cell/single-nucleus genomic data. Duties include quality control and analysis of WES/WGS, scRNA/snRNA-seq, lineage-tracing, copy-number, mutation, ecDNA/tumor-evolution, and clinical/longitudinal datasets; integration of data with specimen and clinical annotations; preparation of figures, tables, methods, and reports; coordination with sequencing cores and UCSF/collaborating investigators; maintenance of code, metadata, and secure data-management practices consistent with lab and University policies; contribution to manuscripts, grant progress reports, and presentations; and training/assisting junior lab members in relevant computational methods. No formal supervisory responsibilities are anticipated.

Required Qualifications:

• Associate Specialist – Master's degree (or equivalent degree) or five to ten years of experience in the relevant specialization, by the time of hire.
• Full Specialist – terminal degree (or equivalent degree) or ten or more years of experience in the relevant specialization, by the time of hire.
• Experience/knowledge in computational biology, bioinformatics, genomics, neuroscience, cancer biology, statistics, computer science, or related field.
• Experience analyzing next-generation sequencing datasets.
• Proficiency in R and/or Python and Linux/Unix command-line environments.
• Ability to implement reproducible workflows, document code and analyses, manage research data securely, troubleshoot computational pipelines, and communicate quantitative results to multidisciplinary research teams.
• Applicant's materials must list (pending) qualifications upon submission.

Preferred Qualifications:

• PhD or equivalent research experience in computational biology, genomics, neuroscience, cancer biology, statistics, or a related field.
• Experience with single-cell or single-nucleus RNA-seq, WES/WGS, somatic mutation and copy-number analysis, tumor evolution/lineage-tracing, ecDNA or structural-variant analysis, clinical/genomic data integration, workflow managers, high-performance computing, Git/GitHub, and collaborative manuscript/grant preparation.
• Prior work in brain tumors or cancer genomics is desirable.

See Table 24B for the salary range for this position. A reasonable estimate for this position is $78,300 – $201,700.