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 reproducible machine learning models and pipelines for high-performance computing, applying pre-trained and custom algorithms to research and clinical contexts. Lead interdisciplinary teams in defining project objectives, monitoring progress, and publishing findings in peer-reviewed journals while mentoring graduate students and research assistants. Manage complex analytical workflows involving data preprocessing, feature engineering, and validation within Linux environments using version control systems.
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.)
Hiring someone like this?
Get your role in front of qualified candidates on Sorce.