Basis Postdoctoral Fellow — Perception & Model Discovery

The Vondrick group studies computer vision and machine learning. By training machines to observe and interact with their surroundings, we aim to create robust and versatile models for perception. We often investigate visual models that capitalize on large amounts of unlabeled data and transfer across tasks and modalities. Other interests include scene dynamics, sound and language and beyond, interpretable models, and perception for robotics.

Our group is part of the Visual Computing and Machine Learning ecosystem at Columbia.

This is a joint postdoctoral position between Basis and the Vondrick group at Columbia, and is funded in part by the NSF’s AI Institute for Artificial and Natural Intelligence (ARNI)  fellow will join an existing project team, whose aim is to build embodied artificial agents that can perform model discovery and reasoning in the real world. Achieving this aim demands advances in perception, representation, and reasoning over existing algorithms.

The position offers an immersive research environment for highly qualified researchers to deepen their expertise in computational theories of intelligence, including but not limited to perception, reasoning, learning, and decision-making.

• Researchers holding a PhD in technical areas such as statistics, programming languages, machine learning, computational neuroscience, cognitive science, physics, or mathematics.
• Experience in computer vision, perception for robotics, and/or active inference is particularly relevant.
• Individuals with a demonstrated track record in scientific research, which can be evidenced through publications, technical reports, or impactful software projects.

• Conduct independent and collaborative research, focusing on understanding and building embodied artificial intelligence.
• Disseminate research findings through academic publications and presentations at leading conferences.
• Actively engage in knowledge transfer within Basis and Columbia, converting research into actionable insights and algorithms.
• Provide mentorship to junior team members and contribute to the scientific discourse through seminars, workshops, and collaborative projects.

• FT/PT:
  This is a full-time, time-bound fellowship lasting between 1 to 2 years.
• Location:
  
  Limited to the New York City area; this is an in-person position.
• Salary:
  Competitive with leading postdoctoral fellowships.
• Application close date:
  The close date has passed (1/3/24), and we are currently considering applications. New applications may still be submitted at this time, but we do not guarantee that they will be considered.