The Computation and Psycholinguistics Lab at Johns Hopkins University (caplabjhu.edu), directed by Tal Linzen (tallinzen.net<https://caplabjhu.org/www.tallinzen.net>), is seeking to hire two post-doctoral researchers. Research in the lab lies at the intersection of linguistics, psycholinguistics and deep learning (for a survey of some of the areas of research in the lab, see http://tallinzen.net/media/papers/linzen_2019_language.pdf). One of the positions will involve linguistically-informed studies of syntax and semantics in neural networks, and/or latent variable neural network models. The other position will involve modeling human neural recordings using artificial neural networks, as part of a collaboration with Christopher Honey (https://www.honeylab.org/).

Both positions are available immediately, and start date is flexible; applications will be reviewed on a rolling basis. The initial appointment will be for one year, with the opportunity for renewal thereafter. We especially encourage applications from women and members of minorities that are underrepresented in science.
See below for details about the individual positions. Please feel free to email Tal Linzen (EmailEmail>) with any questions.


For this position, there is considerable flexibility as to the specific topic of research. Potential areas include:

* Studying syntactic and semantic generalization across languages and neural network architectures. This topic is particularly well-suited to candidates with a strong background in syntax, semantics or psycholinguistics and significant computational skills; it does not require existing expertise in neural networks.

* Developing neural network models that learn syntax from the input available to a child and/or match human comprehension and reading behavior.

The training environment will span the Departments of Cognitive Science and Computer Science. The postdoctoral researcher will be affiliated with the Center for Language and Speech Processing (CLSP), one of the world’s largest centers for computational linguistics; collaborations with other groups at CLSP will be encouraged. The candidate will have access to extensive computational resources through the Maryland Advanced Research Computing Center, as well as an eye-tracker for running behavioral experiments, if relevant to the project.

Candidates should have a PhD in a relevant field (including, but not limited to, linguistics, psychology, cognitive science and computer science) by the start date. To apply, please email a cover letter (including a brief summary of previous research accomplishments and future plans), a current CV, and a relevant publication to Email. In the CV or cover letter, please include contact information for three references.
The goal of this project is to use state-of-the-art artificial neural networks to understand the mechanisms and architectures that enable the human brain to integrate linguistic information at the levels of syllables, words and sentences. For this purpose, the project lead will have access to high-fidelity intracranial recordings from the surface of the human brain, as people process sentences and narratives. In parallel, this project is expected to generate new computational models and analytic methods for natural language processing, informed and constrained by human data.

Johns Hopkins is home to a large and vibrant community in neuroscience and computational linguistics, and the training environment will span the Departments of Cognitive Science, Psychological and Brain Sciences, and Computer Science. The postdoctoral researcher will be affiliated with the Center for Language and Speech Processing, one of the world?s largest centers for computational linguistics.

For candidates who wish to collect new human data, Hopkins provides a top-notch neuroimaging center, including 3T and 7T scanners; new TMS and EEG facilities housed in the PBS department; and access to human intracranial experiments via neurology collaborators in Baltimore and Toronto. The postdoctoral researcher will have access to a large number of GPUs for training neural networks and other computational models through the Maryland Advanced Research Computing Center.


Johns Hopkins University


Candidates should have (i) a PhD in a relevant field (e.g., linguistics, cognitive science, neuroscience, physics, psychology, mathematics, or computer science) by the start date; (ii) a publication record that includes computational modeling and empirical data analysis. The ideal candidate will have a combined background in computational linguistics, machine learning and neuroscience.

Educational level:

Ph. D.

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