Post-Doctoral Fellow
$60,000–$79,000 year
HybridNew York City, New York, United States or New York, United States
Job Summary
Design, document, and execute research studies evaluating mental health signals from multimodal data sources including digital journaling, surveys, and biometrics. Develop machine learning models and analytical pipelines to validate these signals, ensuring reproducible code with version control and responsible handling of sensitive data. Publish findings in peer-reviewed journals, present at conferences, and contribute to grant proposals while mentoring graduate students and junior team members. Collaborate with interdisciplinary teams to define objectives, monitor progress, and drive strategic research direction.
Required Qualifications
- PhD in Neuroscience, Psychology, Engineering, Computer Science or similar domain
- 4+ years of experience in data analysis and data science fundamentals (e.g., algorithms, data structures, data visualization, machine learning), preferably in a clinical or research setting
- 4+ years of experience including education in at least one scientific programming language (e.g., Python/R, Matlab) and related toolboxes or frameworks (e.g., Tidyverse, Scipy, Sklearn, Polars, Pytorch)
- 2+ years of experience including education working in a Linux environment, using version control systems (e.g., GitHub), and software virtualization platforms (e.g., Docker)
- 2+ years of practical experience designing and developing ML and NLP technologies using ML and NLP toolchains (e.g., pytorch, tensorflow, SpaCy, HuggingFace, NLTK.)
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