Associate Specialist - Ntranos lab

Associate Specialist - Ntranos lab

The Ntranos lab in the UCSF Diabetes Center is seeking to hire a Research Specialist. This Specialist's effort will be focusing on collaborative projects with an overlapping job description along with jointly developed expectations and mentorship. The Specialist will aid in the lab's computational methods development efforts and provide essential bioinformatics support in the analysis of various experimental data modalities, including single-cell RNA-seq and spatial transcriptomics.

The Ntranos lab focuses on computational methods development at the intersection of genomics, machine learning and AI. Our research revolves around key algorithmic and statistical challenges that arise in computational biology - and is highly collaborative, spanning multiple biological domains in immunology, human genetics, and cancer biology. The Ntranos lab is integrated within the broader computational research community at UCSF as part of the Dept. of Epidemiology & Biostatistics, the Bakar Computational Health Sciences Institute, and the Institute of Human Genetics.

The successful applicants will have strong computational backgrounds and a documented record of professional achievement in the form of publications and conference presentations. Individuals must also be familiar with data science and reproducible research workflows, as well as mathematical concepts in linear algebra and statistical modeling. Expectations also include good oral/written communication skills, creative problem-solving know-how, an outstanding sense of teamwork and scientific collaboration, and the ability to integrate detailed analyses into a larger disease-oriented context. The Specialist is expected to be a problem-solver with a positive attitude who can critically analyze data, and assume primary responsibility for communicating scientific results, with a high level of independence and an ability to benefit from focused feedback.

Required Qualifications

• Excellent organizational and interpersonal communication skills (verbal and written).
• Willingness and ability to quickly learn new scientific methods and skills in the context of changing research priorities.
• Ability to work independently and as a member of an interdisciplinary research team.
• Ability to prioritize tasks, coordinate work with others, and meet multiple deadlines.
• Master's degree (or equivalent degree) in academic fields related to computational biology and bioinformatics (e.g., Systems Biology, Data Science, Computer Science, etc.) or five to ten years of experience in bioinformatics and computational biology research, by the time of hire.
• Direct hands-on experience in bioinformatics and computational biology research.
• Proficiency in both Python and R programming languages, with expertise in Unix and Bash scripting, and extensive experience working with high-performance computing (HPC) servers.
• Applicants' materials must list current and/or pending qualifications upon submission.

Preferred Qualifications

• Familiarity with basic data science workflows and statistical modeling applications is required; expertise is strongly preferred

Please apply online at https://aprecruit.ucsf.edu/JPF05292.

See Table 24B for the salary range for this position. A reasonable estimate for this position is $73,000 - $85,000.

• 3 required (contact information only)

As a University employee, you will be required to comply with all applicable University policies and/or collective bargaining agreements, as may be amended from time to time. Federal, state, or local government directives may impose additional requirements.

UC San Francisco seeks candidates whose experience, teaching, research, or community service has prepared them to contribute to our commitment to diversity and excellence. The University of California 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, disability, age or protected veteran status.