Research Assistant

Overview

Job Summary focuses on the organization, management, and archiving of research data for a variety of studies, projects, and initiatives. Supports research programs by ensuring data integrity, accessibility, and compliance with institutional guidelines for secure data handling and storage. Assists with the development and implementation of data management protocols, maintains detailed documentation of data workflows, and collaborates with research team members to ensure proper data organization and version control.

Provides support for data queries, tracking, and updates to facilitate efficient project progression and reporting.

Department Emergency Medicine – Pediatric

• Curate, organize, and archive research data across multiple studies.
• Maintain meticulous version control and data documentation.
• Collaborate with research fellows, data scientists, and faculty on dataset development and preparation for analysis.
• Assist with data exploration, quality control, and troubleshooting.
• Synthesize literature related to trauma, clinical decision rules, and diagnostic imaging.
• Prepare research reports, abstracts, and figures for presentations and publications.

• Bachelor s degree in computer science, data science or related area and/or equivalent experience/training.
• Basic skills to analyze and research information and synthesize large amounts of data with attention to detail.
• Basic program and project management skills.
• Ability to monitor computing resource usage and costs, ensure the project stays within budget, and provide regular spending updates.
• Ability to meet precise deadlines and be part of a fast-paced, self-directed team with minimal supervision.
• Technical proficiency in standard Microsoft Office software and ability to learn UCSF computational resources for secure data hosting and computing services.
• High integrity and strong work ethic.
• Skills to learn organization-specific and other computer application programs; strong written and verbal communication skills; ability to maintain confidentiality and exercise sound judgment.

• Analytical abilities and familiarity with programming tools including Python (Pandas, Scikit-Learn, OpenCV, PyTorch), R, SQL, HTML/CSS, C, STATA.
• Coursework in Machine Learning, Algorithms/Advanced Data Structures, Data Science, Probability, Data Graphics and Visualizations, Modern Regression, Technical Writing, High Dimensional Inference.
• Familiarity with software such as MS Office, Tableau, Figma, Smartsheets, MD.Ai, REDCap.

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.

UCSF values professionalism, respect, integrity, diversity, and excellence. UCSF is committed to equity and building a broadly diverse community, nurturing a culture that is welcoming and supportive, and engaging diverse ideas for high-quality education, discovery, and patient care. More information is available f.edu.

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
• Work Style
  :
  Fully On-Site
• Shift
  :
  Days
• Shift Length
  : 8 Hours
• Additional Shift Details
  :
  Monday - Friday 8:30am – 5:00pm with some variable hours

Salary range: $52,800 - $64,500 (Annual Rate). Salary and offer components are subject to approvals based on UC policy. Placement within the range depends on work experience and internal equity within this position classification at UCSF.

To learn more about UCSF benefits, please visit: (Use the "Apply for this Job" box below)..html