Basis Postdoctoral Fellow - Collaborative Intelligent Systems Project
 Society for Neuroscience | |
 United States, Massachusetts, Cambridge | |
 Nov 19, 2024 | |
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Basis Postdoctoral Fellow - Collaborative Intelligent Systems Project
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Basis Postdoctoral Fellow - Collaborative Intelligent Systems Project ThisBasis Postdoctoral Fellowshipsupports postdocs joining the Collaborative Intelligent Systems project, which aims reason about a large class of collaborative behaviors, spanning a broad range of species and contexts. You will be mentored byEmily Mackevicius. In addition, you may select a co-mentor external to Basis. Fellowships will start in March 2025, for two years with possibility of extension. We will begin reviewing applications on Nov 20, 2024, and hope to extend offers by Dec 13, 2024. Apply Now About Basis Basisis a nonprofit applied AI research organization with two mutually reinforcing goals. The first is tounderstand and build intelligence.This entails establishing the mathematical principles of reasoning, learning, decision-making, understanding, and explaining, and constructing software that embodies these principles. The second is toadvance society's ability to solve intractable problems.This involves expanding the scale, complexity, and breadth of problems we can solve today and, more importantly, accelerating our ability to solve problems in the future. To achieve these goals, we are building both a new technological foundation inspired by human reasoning, and a new type of collaborative organization that prioritizes human value. About Emily Mackevicius Emily Mackevicius is a co-founder and director of Basis Research Institute, where she leads the Collaborative Intelligent Systems group. She did her postdoctoral work studying memory-expert birds in the Aronov lab and the Center for Theoretical Neuroscience at Columbia, and her PhD work studying how birds learn to sing in the Fee lab at MIT. She is interested in how intelligent behaviors emerge, especially in distributed and recurrent systems. Her theoretical work is strongly grounded in experimental practice, currently high-resolution behavioral recordings of groups of animals foraging in environments ranging from NYC parks and subways to Arctic Alaska. About the Collaborative Intelligent Systems group Many of humanity's greatest accomplishments and failures have been determined by our ability or failure to collaborate. As global collaborative systems face unprecedented human-induced changes, there is an urgent call for stewardship akin to the measures demanded by climate change. Beyond humans, it is essential to understand collaborative behaviors across different species, and how properties of an ecosystem affect, and are affected by, the behavior and nervous systems of each animal. We create software tools for understanding and reasoning about collaborative intelligent systems (see our github repo,collab-creatures). We're developing analysis tools to work on datasets from a broad range of species and environments, collected by our team as well as collaborators. The datasets we collect capture high-resolution movement of groups of animals, as well as 3D geometry of the environment. Our approach involves integrating and synthesizing knowledge across different disciplines, species, and spatiotemporal scales (see ourfirst paper). We aim to produce accessible open-source software tools that empower scientists, policymakers, and the public to make more informed decisions about collaborative intelligent systems. Who we're looking for
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