Research Scientist

Child Mind Institute•New York, NY

8h•Hybrid

About The Position

We're dedicated to transforming the lives of children and families struggling with mental health and learning disorders by giving them the help they need. We've become the leading independent nonprofit in children's mental health by providing gold-standard evidence-based care, delivering educational resources to millions of families each year, training educators in underserved communities, and developing tomorrow's breakthrough treatments. As part of the DAIR team, you will report to the Director, DAIR. You will help provide oversight for the development, implementation and analysis of multimodal modal brain and body imaging (MoBI) studies of behavior and brain function with particular focus placed on the application of advanced statistical learning techniques to multimodal datasets for the purpose of identifying biomarkers, signals, or trends that have clinical utility. Translational models will be employed as needed to understand phenomenology underlying biomarkers and establish their validity. The Research Scientist will help develop short- and long-term work goals for data analysts and provide supervision and mentoring for junior research staff. The Research Scientist will ultimately function as a Principal Investigator, providing leadership in these areas and building a portfolio of scientific evidence, fundable projects, and software and analytic tools in the area of multimodal brain and body imaging and biometrics. This is an exempt, full-time, hybrid position located in our NYC headquarters office or other relevant location. This position requires a minimum of four (4) days per week in the office, on a schedule determined by your supervisor. The in-office requirement and schedule are subject to change based on the needs of the program and the organization.

Requirements

PhD in electrical engineering, bioengineering, computer science, biophysics, appliedmathematics, or neuroscience, with two years or more of postdoctoral training in one ormore measurement modalities for brain function (inclusive of training, if applicable).
5+ 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.
5+ years of experience in at least one scientific programming language (e.g., Python/R,Matlab) and related toolboxes or frameworks (e.g., Tidyverse, Scipy, Sklearn, Polars,Pytorch) is required.
5+ years of combined experience and education in the collection and/or analysis of mental health-related data modalities, such as MRI, EEG, physiological measures, eye-tracking, developing computer-based tasks, or ecological assessments.
2+ years of supervising experience by mentoring predoctoral trainees
Must be considered NIH-eligible to serve as a Principal Investigator on grant submissions.
Must have a demonstrable track record of conducting experiments, writing analyses, and communicating results through scientific posters, presentations, and papers.
Must be broadly considered a strong and qualified researcher in signal processing, image analysis, and software development.
An outstanding academic and research background in a disciplinary area relevant to the Child Mind Institute, including relevant academic qualifications.

Responsibilities

Procurement and development of multimodal dataacquisition protocols.
Development, application, and refinement of analytic approaches for multimodal data.
Prepare manuscripts for publication in peer-reviewed scientific journals.
Prepare grant applications directly as principal and co-investigator.
Assistance in the guidance and mentoring of DAIR and MoBI team research staff (e.g.,research assistants, data analysts, post-doctoral fellows).
Strategic planning and oversight for the development and qualityassurance for DAIR and MoBI team research databases and related infrastructure.
Formation and maintenance of collaborative relationships with scientific peers.
Perform additional job-related responsibilities as assigned