Postdoctoral Fellow in AI and Cognitive Science

The Language Creation and Learning Laboratory (PI Annemarie Kocab) in the Department of Cognitive Science at Johns Hopkins University seeks an outstanding postdoctoral fellow to lead scientific efforts on machine learning applications to signed languages to begin by Fall 2026.

The fellow will work on research projects spanning evaluation of deep learning neural networks trained on signed language recognition. The fellow will work closely with the PI Annemarie Kocab and collaborator Alex Lu, Senior Researcher at Microsoft Research. Duties will include:

• Design, execute, and troubleshoot experiments
• Develop and validate benchmarks for model evaluation
• Contribute to the development of datasets for model training and evaluation
• Mentor and supervise graduate and undergraduate students
• Prepare progress reports and present results to collaborators
• Publish findings in peer-reviewed journals and conference proceedings
• Contribute to competitive grant proposals to federal agencies (e.g., NIH)

Required Qualifications

• PhD in Cognitive Science, Computer Science, Psychology, Linguistics, or related fields
• Ability to move to and work at Johns Hopkins University, USA
• Demonstrated track record of first-author publications and presentations
• Experience with computational methods and machine learning, including but not limited to deep learning, computer vision, computational linguistics, pretraining methods, interpretability, and transfer learning
• Experience with cognitive science, particularly psycholinguistics or linguistics
• Proficiency in data analysis and computational tools; strong programming skills (e.g., MATLAB, Python, or equivalent)
• Ability to lead research projects and collaborate with experimentalists
• Strong written and oral communication skills

Preferred Qualifications

• Experience with human computer interaction, accessibility, or AI fairness and ethics

Submit a cover letter, CV, sample of work, and 3 letters of reference to Interfolio.

Salary Range

The referenced salary range represents the minimum and maximum salaries for this position and is based on Johns Hopkins University's good faith belief at the time of posting. Not all candidates will be eligible for the upper end of the salary range. The actual compensation offered to the selected candidate may vary and will ultimately depend on multiple factors, which may include the successful candidate's geographic location, skills, work experience, internal equity, market conditions, education/training and other factors, as reasonably determined by the University.

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Background Checks

After receiving a conditional offer, the successful candidate(s) for this position will be subject to a pre-employment background check including education verification. When deciding whether a candidate's conviction history is job-disqualifying, the University considers the nature and gravity of the offense, the time that has passed since the conviction, and the nature of the job being sought.

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