[visionlist] [jobs] Researcher in Computer Vision / ML for human driver understanding and interactions

[Guy Rosman]

(Pls excuse cross-postings)


Our team at TRI is seeking a research scientist for research at the
intersection of machine learning, computer vision, and human factors. The
role focuses on ML approaches for understanding, detecting, and developing
intervention strategies for driver impairments, such as cognitive
distraction and intoxication. The ideal candidate will contribute to
fundamental research, publish in top-tier venues, and build machine
learning models and prototypes that integrate human-in-the-loop data
towards novel approaches for understanding and assisting drivers under
diverse situations. The candidate will be part of a team of computational
and cognitive researchers, devising and testing ML approaches on a variety
of data sources and human-in-the-loop experiments

This is an opportunity to work on cutting-edge research in human-robot
interaction and intelligent vehicle systems in a collaborative and
interdisciplinary team of experts in robotics, AI, and human factors. You
will have access to state-of-the-art robotic platforms and simulation tools
with the potential to contribute to academic publications and impactful
real-world applications.

Apply at: https://jobs.lever.co/tri/89f860cc-13bd-4332-81f6-c2528d20a100

Or contact me for questions.

Thanks,

Guy Rosman

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Responsibilities

   -

   Conduct original research on driver impairment detection and
   intervention (e.g. warning, coaching, actuation) using machine learning and
   computer vision.
   -

   Develop algorithms and models to analyze driver behavior, physiological
   signals, and other multimodal inputs.
   -

   Design, implement, and conduct human-in-the-loop behavioral studies,
   ensuring robustness and real-world applicability.
   -

   Publish findings in high-impact conferences and journals.
   -

   Collaborate with interdisciplinary teams, including human factors
   experts, cognitive scientists, and engineers.
   -

   Prototype and validate ML-based intervention strategies to enhance
   driver safety and performance.

Qualifications

   -

   PhD in Computer Vision, Machine Learning, Human-Centered AI, or a
   related field.
   -

   Research experience in human and machine vision, behavior analysis, or
   multimodal learning.
   -

   Strong publication record in top-tier conferences and journals (e.g.,
   CVPR, NeurIPS, ICCV, ICLR).
   -

   Experience working with human-in-the-loop data: data collection,
   annotation strategies, and model training.
   -

   Proficiency in deep learning frameworks (e.g., PyTorch, Jax, Hugginface)
   and data analysis tools.
   -

   Ability to work both independently and as part of an interdisciplinary
   team.
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