Dear colleagues,

I'm recruiting at least one post-doc for a project at New York University
aimed at creating language models that process language more like humans than
mainstream LLMs do
<https://tallinzen.net/media/papers/huang_et_al_2024_jml.pdf>. We are
planning to explore architectural modifications, training data
interventions, and steering through interpretability.

One motivation for this project is the empirical finding
<https://direct.mit.edu/tacl/article/doi/10.1162/tacl_a_00548/115371/Why-Does-Surprisal-From-Larger-Transformer-Based>
that the better LLMs become in terms of perplexity and task performance,
the worse they are as cognitive models of how people read and learn
language; we think that to reverse this trend we need to find ways to
constrain them (in terms of e.g. working memory, parse parallelism, and
factual and linguistic knowledge), and improve them in other ways to make
up for these constraints, e.g. through increasing data efficiency
<https://tallinzen.net/media/papers/wilcox_et_al_2025_jml.pdf>.

We're planning to benchmark the models against behavioral and neural data
from humans: eyetracking, fMRI and intracranial recordings. Some of the
data already exists, and some will be collected by collaborators at other
universities specifically for this project. But we also expect to do a lot
of fundamental modeling and interpretability work.

You do not need to have existing experience in cognitive science, but you
should have a strong track record in computational research; and you should
be interested in using AI for science, in learning about cognitive science
and collaborating with linguistics and cognitive scientists, and in doing
open-ended fundamental research on LLMs.

There are no teaching requirements. The position will be renewed every
year, but we expect the funding for this project to last four years. You
will be affiliated with NYU's Center for Data Science, and, if relevant,
also with the department of linguistics. NYU has large NLP and
computational cognitive science communities, with lots of opportunities for
collaborations.

The start date is flexible, though of course you should have a PhD by the
time you start. Your application is most likely to be considered if you
apply before *August 10th.* Please fill out this lightweight form
<https://docs.google.com/forms/d/e/1FAIpQLSc5IwTU43CWVjQYsWbvPkDFH7dFKglqRfPdWRJSvCbYuxlv-A/viewform>
to
express interest, and you can also email me directly if they have any
questions. I'll be at ACL 2025 and am happy to chat about the position. If
you're interested in working together but don't exactly fit the
description, don't hesitate to reach out!

-- 
Tal Linzen <https://tallinzen.net/>
Associate Professor of Linguistics and Data Science
New York University
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