Summer Internship in Causal Intervention
ASSIGNMENT DURATION: 2-4 Months
LABOR CHARGE: DIRECT
SCHEDULED WORK WEEK HOURS: 20-40 hours/week
EDUCATION DESIRED: MS, Ph.D. or pursuing a graduate degree in Computer Science, Computational Social Science, Network Science, Machine Learning, or Applied Math.
ESSENTIAL JOB FUNCTIONS: Assist technical staff in the design, implementation and performance evaluation of algorithms for causal discovery, inference and counterfactual reasoning and simulation applied to problems in counter influence and algorithmic bias.
EXPERIENCE DESIRED: Class projects or work/internship experience in Bayesian inference, probabilistic programming, natural language understanding applied to problems in predictive analytics, crowd computing, and social network analysis.Programming experience with Python, Java, C/C++, R, and/or Matlab. Experience with Apache Spark, YARN, MapReduce or Hadoop.
KNOWLEDGE DESIRED: Probabilistic programing, Bayesian inference, experimental design, strong programming skills, particularly proficient with Python, Java, R, C/C++, and/or Matlab.
ESSENTIAL PHYSICAL/MENTAL REQUIREMENTS: Good communication, presentation and writing skills.
SPECIAL REQUIREMENTS (e.g. driver’s license special tools or restrictions): U.S. citizenship or permanent resident status required.
Selected candidates will be hired through a temporary agency and subject to the agency's pre-employment substance abuse testing.
- Pay Type Hourly
- Employment Indicator Internship
- Malibu, CA, USA