This Basis Postdoctoral Fellowship is a collaborative initiative between Basis Research Institute and Harvard University’s Amin Lab. It also includes collaborators at the Hugh Kaul Precision Medicine Institute. As a fellow, you will be a key contributor to our focused efforts to research and develop fundamental methods in AI to help practitioners, including doctors and civic policymakers, make informed decisions based on vast amounts of data and information.
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.
Nada Amin’s research group is dedicated to advancing the field of programming languages and software engineering. Our primary focus is on exploring and refining type systems, enhancing program synthesis techniques, and expanding the capabilities of metaprogramming to improve software reliability and developer efficiency. We are passionate about developing theoretical foundations and practical tools that enable programmers to write correct and efficient code more easily.
Our research covers a wide range of interests within programming languages, including but not limited to, type-safe metaprogramming, program verification, and the automatic synthesis of programs from specifications. Through our work, we aim to bridge the gap between theoretical computer science and practical software development, making advanced programming language concepts accessible and usable for everyday programming tasks.
Our research aims to develop new foundations and technologies for reasoning and planning that leverage large language models (LLMs) and integrate them with complementary approaches, including program synthesis, and causal and probabilistic programming. The goal is to create integrated systems that harness the deep domain knowledge and emergent capabilities of LLMs, alongside the precision, efficiency, and correctness of formal reasoning frameworks. This could deliver the best of both worlds: the intuitive, context-rich insights of LLMs and the logical, structured analysis provided by formal methods. Key application areas include developing integrated agents that:
Fellows will have the opportunity to develop these tools within concrete projects with real-world impact, leveraging the collective networks of Basis, Harvard, and Hugh Kaul Precision Medicine Institute. Specifically, fellows will be able to contribute to larger initiatives to (i) dramatically advance precision medicine, or (ii) advance society’s capacity to make informed civic policy decisions, building upon Basis work in civic policymaking.
The research environment is both structured and adaptable, with multiple avenues for scholarly contribution. As a fellow, your expertise can shape various aspects of the project. It will deepen your foundations in multiple domains, including large language models, reasoning, planning, and precision medicine or civic policymaking while also allowing for a balance of focused research, academic exploration, and software development.
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