Full Time Neuroimaging Data Analyst Jobs (NOW HIRING)

Job Summary:
Stanford University is seeking a Precision Psychiatry and Neuroimaging Data Analyst with a focus in mental health to manage and analyze large amounts of functional neuroimaging, behavioral and symptom data for classification and prediction of outcomes in depression. The role involves organizing data, implementing machine learning algorithms, and overseeing communication with an external NIH data coordinating center.
Responsibilities:
• Organize neuroimaging and relevant behavioral and clinical metadata in data structures.
• Visualize these data, process neuroimaging data and implement machine learning algorithms and models to these neuroimaging and metadata, including predictive models, latent variable, clustering algorithms and canonical correlation analyses.
• Oversee communication and data sharing with an external NIH data coordinating center.
• Collect, manage, and clean large datasets.
• Employ new and existing tools to interpret, analyze, and visualize multivariate relationships in human subjects’ data.
• Create databases and reports, develop algorithms and statistical models, and perform statistical analyses appropriate to data and reporting requirements.
• Use system reports and analyses to identify potentially problematic data, make corrections, and determine root cause for data problems from input errors or inadequate field edits, and suggest possible solutions.
• Develop reports, charts, graphs and tables for use by investigators and for publication and presentation.
• Analyze data processes in documentation.
• Collaborate with faculty and research staff on data collection and analysis methods.
• Provide documentation based on audit and reporting criteria to investigators and research staff.
• Communicate with grant agencies regarding data sharing centers.
Qualifications:
Required:
• Bachelor's degree or a combination of education and relevant experience. Experience in a quantitative discipline such as economics, finance, statistics, or engineering
• Substantial experience with MS Office and analytical programs
• Strong writing, problem solving and analytical skills
• Ability to prioritize workload and deadlines
• Strong foundation in data structures for management and storage of data
• Expertise in the integration of high dimensional data with meta-data, data quality, and data processing
• Strong knowledge of machine learning algorithms and models, and underlying statistical principles, including predictive models, latent variable modeling (such as drift diffusion modeling), clustering algorithms and canonical correlation analyses
• Hands on familiarity with functional MRI analysis software, such as SPM, FSL and Freesurfer
• Experience with REDCap database architecture, workflow automation, API integration, and scripting to support scalable data capture, quality assurance, operational reporting, and cross-platform research infrastructure
• Proficiency in statistical programming languages such as R and programming languages such as Python
• Familiarity with data visualization and reporting in vector format
• Experience working in research setting relevant to mental health
• Excellent communication and collaboration skills to work effectively with cross-functional teams, including clinical, cognitive, and affective neuroscientists, mental health clinicians, physicians, functional neuroimaging specialists, psychologists and biomedical research engineers
• At least two years of relevant hands-on experience in a quantitative discipline relevant to the domain of the research in the lab, such as psychology, neuroscience, statistics or engineering
• Motivation to contribute to advances in precision mental health
Preferred:
• A multi-year commitment is preferred
Company:
Stanford University is a teaching and research university that focuses on graduate programs in law, medicine, education, and business. Founded in 1885, the company is headquartered in Stanford, USA, with a team of 10001+ employees. The company is currently Late Stage.