is a nonprofit applied AI research organization with two mutually reinforcing goals.
The first is to understand and build intelligence. This means to establish the mathematical principles of what it means to reason, to learn, to make decisions, to understand, and to explain; and to construct software that implements these principles.
The second is to advance society’s ability to solve intractable problems . This means expanding the scale, complexity, and breadth of problems that we can solve today, and even more importantly, accelerating our ability to solve problems in the future.
To achieve these goals, we’re building both a new technological foundation that draws inspiration from how humans reason, and a new kind of collaborative organization that puts human values first.
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 postdoctoral fellowship is a collaborative initiative between Basis Research Institute and Columbia University's Vondrick Lab. Supported in part by the NSF's , the fellowship centers on research at the junction of perception and model discovery. As a fellow, you will be a key contributor to our focused efforts to develop systems capable of autonomously discovering causal models by conducting experiments in the physical environment.
Our research aims to understand and automate the generation of scientific models. This initiative requires integrating several areas—probabilistic inference, active experimentation, and program synthesis—with initial efforts elaborated in . The ultimate objective is to create an AI system capable of understanding the operating rules of real phenomena through directed experiments, and to develop a comprehensive theory of the principles by which it operates.
The research environment is both structured and adaptable, with multiple avenues for scholarly contribution. As a postdoctoral fellow, your expertise can shape various aspects of the project. Examples include developing:
Participation in this fellowship will deepen your foundations in multiple domains of intelligence, including perception, representation, and reasoning, while also allowing for a balance of focused research, academic exploration, and software development.
We’re looking for PhD-holding researchers with the following traits:
Differences
Similarities
Basis will support Fellows pursuing academic positions with mentorship and training regarding the academic job market.
Please submit the following:
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.
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