RSCH DATA ANL 2 RP

University of California, San Francisco
San Francisco, CA, United States
25 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
2 years minimum
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Data Analysis Database Design Python (Programming Language) Machine Learning System Programming Deep Learning Information Technology

Job description

  • Gather, analyze, and interpret a wide variety of research imaging data.
  • Apply mathematical, statistical, and machine learning methods to research datasets.
  • Prepare figures and tables summarizing results in support of research proposals, protocols, and reports.
  • Contribute to scientific manuscripts, publications, and presentations.
  • Maintain and develop research data collection, retrieval, and reporting systems.

Requirements

  • Bachelor’s degree in Mathematics, Computer Science, Statistics, Bioengineering, or a related field; and/or equivalent experience or training.
  • Two years of experience in related research activities.
  • Working knowledge of research functions to perform research data analysis.
  • Working skills in statistical analysis, systems programming, and database design to perform research data analysis.
  • Experience with MR data processing and analysis.
  • Experience with Python programming.
  • Experience with Deep Learning/AI programming.
  • Ability to effectively manage time, prioritize multiple projects, and meet deadlines.
  • Strong verbal and written communication skills with the ability to communicate complex information clearly and concisely.
  • Ability to work under general supervision.
  • Strong ability to work collaboratively in a team environment, demonstrate initiative, maintain flexibility, and adapt to changing priorities.

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Good distractions

Talks and stories from around this role — technically off-topic, practically not.

1:48 min

Automating exploratory data analysis within training pipelines

Dora Petrella · World Congress 2023

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Distinguishing artificial intelligence from deep learning

Sam Witteveen · Coffee With Developers

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Design principles for optimizing distributed application structures

Wei Hu Wei Hu · World Congress 2025

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Background on the Data Lab and organizational structure

Álvaro Martín Lozano · LIVE

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Performing exploratory data analysis to uncover underlying patterns

Julian Joseph · LIVE

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Balancing data science skillings alongside systems engineering rigor

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