[CogSci] Fully-funded PhD positions in Human & Machine Intelligence (Neuro & AI) at Boston College

[Momchil Tomov]

How does the brain support adaptive decision making in the real world?

Recent advances in AI have provided us with models that rival humans on
challenging naturalistic tasks and can serve as starting points for
tackling this question head-on. At the same time, as frontier AI labs push
the limits of scaling laws, many doubt whether more data and compute alone
will lead to human-level learning, planning, and generalization.

The new *Human & Machine Intelligence Lab* at *Boston College* is
recruiting *1-2 PhD students* to work on reverse-engineering naturalistic
learning and decision making in the brain. Specifically, we aim to
understand:

1. How the human brain *learns* internal models of complex, naturalistic
environments.
2. How it uses these models to *plan* toward distant goals.
3. How it *generalizes* this knowledge to new environments.

Building on recent work in theory-based RL [1], you will tackle these
questions by leveraging state-of-the-art AI models (e.g., DDQN, MuZero,
LLMs/VLMs) to analyze behavioral, fMRI, and MEG data from human subjects
engaging in rich tasks, such as learning to play new video games. You will
also have the opportunity to design and conduct experiments
(behavior/fMRI/MEG) to test your hypotheses.

The lab is led by *Momchil Tomov* (starting in Fall 2026) and is joint
between the *Department of Psychology & Neuroscience* and the *Department
of Computer Science*.

*Why Boston College?*

Boston College is an elite R1 research institution in the heart of the
Boston metropolitan area. Greater Boston is a powerhouse of innovation,
home to over 35 colleges and universities – including Harvard and MIT – and
a thriving ecosystem of AI & biotech startups. As a PhD student, you will
be immersed in this vibrant research community while enjoying the benefits
of living in a diverse, bustling metropolis. For the outdoors-inclined, New
England offers scenic opportunities to escape city life: from sailing on
the Charles River, to hiking or skiing in the White Mountains, to surfing
off the shores of Rhode Island, to enjoying freshly caught oysters on Cape
Cod.

*Position Details*

   - Lab: Human & Machine Intelligence
   - PI: Momchil Tomov
   - Website: www.momchiltomov.com
   - Contact: mtomov+cogsci at g.harvard.edu
   - Stipend: $45,000 / year (fully-funded)
   - Start date: September, 2026

*Application*

   - Deadline: *December 15, 2025*
   - Department of Psychology & Neuroscience: [*APPLY HERE
   <https://www.bc.edu/content/bc-web/schools/morrissey/departments/psychology-neuroscience/graduate.html>*
   ]
   - Department of Computer Science: [*APPLY HERE
   <https://www.bc.edu/bc-web/schools/morrissey/departments/computer-science/academics/phd.html>*
   ]

*Requirements*

The ideal candidate has experience with state-of-the-art RL
models/LLMs/VLMs and/or experience analyzing behavioral/neural data.
Experience collecting fMRI/MEG data is a plus.

Please do not hesitate to reach out with questions! We also encourage you
to forward this to anyone who might be interested.

*References*

[1] Tomov, M. S., Tsividis, P., Pouncy, T., Tenenbaum, J. B., Gershman, S.
J. (2023). “The neural architecture of theory-based reinforcement
learning.” *Neuron* 111 (2): 454-469.
https://doi.org/10.1016/j.neuron.2023.01.023
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