[Human-Machine Interaction] Human Behavior Modeling

[Human-Machine Interaction] Human Behavior Modeling

Job Number: P20INT-35
This position focuses on behavioral model for social human machine interaction (interacting with regular or L2 automated vehicles). The project involves human behavior pattern recognition, development of behavioral model using probabilistic models. You are expected to:
San Jose, CA
  • Define behavioral patterns and conduct recognition analysis.
  • Reasoning of causalities between human characteristics with specific behavioral patterns.
  • Build behavior modeling framework to understand and predict interactions between human and machine.
  • Develop more usable machine/deep learning tools for improve system performance and mobility safety.

Qualifications:

  • Highly qualified M.S. candidate in human behavior related field (human computer interaction, human factor engineering, cognitive science), psychology, or social science, statistics or operation/industrial engineering.
  • Familiarity with human-machine interface, interaction/behavioral modeling for automobiles.
  • Knowledge in multivariate statistical methodologies e.g. causal inference with observable data, longitudinal analysis, classification, dimension reduction, clustering, hierarchical linear (random effects) modeling.
  • Experience in machine learning algorithms.

Bonus Qualifications:

  • Ph.D. candidate in computer science, electrical engineering, mathematics, statistics, psychology, cognitive science or human behavior related field in Applied Statistics, Mathematics, Psychology, Cognitive Science and Human Computer Interaction.
  • Experience in applied statistics i.e. probabilistic models and Bayesian models, machine/deep learning.

Duration: 3 months

How to apply

Candidates must have the legal right to work in the U.S.A.​ Please add Cover Letter and CV in the same document

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