Post-Doctoral Fellow

About the role

The Post-Doctoral Fellow in the Center for Data Analytics, Innovation, and Rigor (DAIR Center) will lead the development of machine learning models and conduct advanced data analyses, focusing on digital journaling, survey, cognitive, biometric, and/or multimodal data types. Responsibilities include designing, documenting, and conducting experiments to evaluate meaningful signals of mental health from multimodal data sources, developing analytical models to assess the validity of these signals, and publishing findings in peer-reviewed scientific journals.

This is an exempt, full-time, hybrid position located in our NYC headquarters office. The in-office requirement and schedule are subject to change based on the needs of the program and the organization. This position requires a minimum of four (4) days per week in the office, on a schedule determined by your supervisor.

Responsibilities

• Lead the design and execution of research studies involving complex analytical workflows including data preprocessing, feature engineering, model development, scientific analyses, data visualization, and validation.
• Develop reproducible, scalable, well-documented code and pipelines suitable for high-performance computing ecosystems, with version control through GitHub or equivalent repositories.
• Apply both pre-trained and custom-made machine learning models and data manipulation pipelines to research and clinical contexts, ensuring the responsible handling of sensitive data.
• Write, submit, and publish research findings in peer-reviewed scientific journals, present findings at conferences, and contribute to the preparation of grant proposals and funding applications.
• Mentor and provide guidance to graduate students, research assistants, and junior team members on research methodologies and data analysis techniques.
• Collaborate with interdisciplinary research teams to define project objectives, establish timelines, monitor progress, and ensure successful completion of research milestones while contributing to the intellectual direction of the team through participation in research planning meetings and strategic discussions.

Requirements

• 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.).

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.).

Skills

• Strong background in machine learning and data science.
• Experience with scientific programming languages and related toolboxes/frameworks.
• Proficiency in Linux environments and version control systems.
• Experience with ML and NLP technologies.

Benefits

Our great compensation package and benefits include medical insurance, 401(k), paid parental leave, dependent care, discounted tickets and entertainment perks programs.

Pay

The salary range for the position is posted. Factors such as candidate's work experience, education/training, job-related skills, internal peer equity, as well as market and business considerations affect the salary offered within this range. In addition, this salary may be subject to a geographic adjustment (according to a specific city and state and depending on the role), if an authorization is granted to work outside of the location listed in this posting.