Job Details

Computational and Data Science Specialist

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Job Summary

The Division of HIV, Infectious Diseases and Global Medicine at Zuckerberg San Francisco General Hospital (ZSFG) is an internationally recognized global leader in HIV clinical care, research and education and has grown to encompass a network of specialty clinics, multiple research and clinical trials, an infectious diseases/HIV education program, an international research program in East Africa and a vibrant community forum for clinicians and researchers.

Dr. Lee's research group ( focuses on clinical and translational research, particularly observational cohort and clinical trial studies that focus on infectious diseases, such as HIV and SARS-CoV-2. The Senior Computational and Data Science Research Specialist will work at an independent level to assist the Principal Investigator in running the computational aspects of Dr. Lee's research group. The incumbent will aid in designing and implementing data analysis methods to analyze a wide range of multidisciplinary projects, including host genome–wide (e.g., whole genome sequencing, GWAS microarray), single‑cell sequencing (e.g., 10X scRNA/VDJ/ATAC/antibody), pathogen‑specific assays (e.g., HIV reservoir quantification by droplet digital PCR, HIV‑host integration PCR assays) and applying advanced statistical modeling approaches to these data (e.g., linear and nonlinear mixed‑effects modeling, causal inference modeling). The incumbent will directly perform complex analyses applying novel computational methods, manage the research group's server space (UCSF Wynton HPC cluster), assist in overseeing and mentoring trainees and be a major part of bringing the analysis projects to completion.

Requirements include a strong background in biostatistics, statistical genetics, and single‑cell sequencing bioinformatics. Interpersonal and communication skills are required to interact with interdisciplinary collaborators. There is potential to help build and support the new CFAR Bioinformatics Core and to travel to HIV cure conferences. The role also carries a strong social‑justice component, directly contributing to projects focused on improving health outcomes.

Required Qualifications

• Master's degree in Math/Statistics/Computer/Computational/Data Science, or Domain Sciences with computer/computational/data specialization or equivalent experience and three or more years of relevant experience. Strong preference for those with experience in causal inference modeling.
• Intermediate knowledge of HPC/data science/CI.
• Advanced skills and 2-3 years demonstrated experience in bioinformatics, computational biology, physics, mathematics, and/or statistical genetics, related to HPC hardware and software power, performance analysis, design, modification, implementation, deployment of HPC or data science or CI applications and tools.
• Demonstrated ability to regularly interface with management.
• Ability to work independently; strong sense of accountability for work; attention to detail; strong interpersonal skills; excellent verbal and written communication skills; ability to multi‑task in a fast‑paced environment.
• Demonstrated effective communication and interpersonal skills.
• Proven skills and experience in independently resolving broad computing/data/CI problems using basic principles.
• Self‑motivated and able to work well independently and as part of a team.
• Thorough experience working in a complex computing/data/CI environment.
• Proven ability to successfully work on multiple concurrent projects.
• Proven ability to understand research computing/data/CI needs, map use cases to requirements, develop and implement solutions.
• Demonstrated broad experience in optimizing, benchmarking, HPC performance, power modeling, analysis of hardware, software, applications for HPC/data/CI.
• Demonstrated experience and ability to collaborate effectively with all levels of staff.
• Solid technical understanding and proficiency with programming languages (e.g., R, Python, Perl, Matlab, C/C++) and SQL.
• Expertise in working with genomic, transcriptomic, and/or immunologic data and relevant analytic tools (e.g., PLINK, SKAT, R Seurat, FlowJo).
• Strong demonstrated ability to deliver high quality work with attention to detail and the ability to meet strict deadlines.

Preferred Qualifications

• Strong preference for PhD experience, especially in causal inference modeling; PhD in Math/Statistics/Computer/Data Science or equivalent.
• Ease with handling large datasets (>1 terabyte) and working within Linux‑based cloud computing clusters.
• Prior laboratory‑based experience and training in biology, immunology, genetics and molecular biology techniques.
• Humanitarian‑minded.
• Previous experience working with clinical datasets related to HIV, COVID‑19 or other infectious diseases.
• Demonstrated ability to contribute research and technical content to grant proposals and manuscript submissions.
• Excellent writing skills as evidenced by prior research publications.

Salary

The salary range for this position is $97,100–$115,000 (Annual Rate).

Benefits

To learn more about the benefits of working at UCSF, including total compensation, visit UCSC Benefits.

Equal Employment Opportunity

The University of California is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected status under state or federal law.

Location

San Francisco, CA
Campus: Zuckerberg San Francisco General (ZSFG)

Employment Type

Full‑time, Hybrid – M‑F, 8 am – 5 pm; onsite and remote.

Job Code

006104 CMPTL AND DATA SCI RSCH SPEC 3

Contact

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