Postdoctoral Fellowship - Collaborative Intelligent Systems

Basis

Postdoctoral Fellowship - Collaborative Intelligent Systems

Cambridge, MA
Full Time
Paid
  • Responsibilities

    About the Fellowship

    This Basis Postdoctoral Fellowship supports 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 by Emily 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.

    PhD students interested in 3-4 month internship positions prior to graduating are encouraged to apply here.

    About Basis

    Basis Research Institute 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.


    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 our first 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

    • Researchers holding a PhD in neuroscience, cognitive science, behavioral science, computer science, artificial intelligence, machine learning, or related fields.
    • Experience in the following research areas highly valued: analyzing animal behavior using AI / machine learning / computer vision techniques; theoretical modeling of cognition; natural behavior / neuroethology; developing AI systems that combine neural and symbolic methods; probabilistic programming.
    • Strong programming skills, including experience developing novel approaches, and contributing to larger codebases.
    • Demonstrated track record in scientific research, evidenced through publications, technical reports, or impactful software projects.

    Core Responsibilities

    • Conduct independent and collaborative research focused on the Collaborative Intelligent Systems project.
    • Analyze multi-agent multi-species behavioral data, including fieldwork datasets collected at Basis, as well as open-source datasets, and datasets from collaborators.
    • Coordinate research with collaborators and Basis Core Tech team.
    • Disseminate research findings through open-source code, academic publications, and/or presentations at leading conferences.
    • Provide mentorship to junior team members and contribute to the scientific discourse through seminars, workshops, and collaborative projects.

    Role Details

    • Full-time: This fellowship is full-time and has duration of 2 years with possible extension.
    • Location: Applicants should reside in, or be willing to relocate to, the Cambridge, MA area. This is an in-person position. You will be expected to travel periodically, funded by Basis, about once every six to eight weeks, for Basis-wide in-person events, typically in New York City.
    • Salary: Competitive with leading postdoctoral fellowships.
    • Start date: March 2025.