Postdoctoral Fellow-MSH-13400-372
About The Position
CentileBrain is a neuroinformatics project that develops normative models and centile-based benchmarks for brain measures across the lifespan. The project integrates large-scale neuroimaging datasets, advanced statistical modelling, machine learning and reproducible computational workflows to support individual-level and group-level interpretation of brain structure and connectivity. The main goal of the project is to advance CentileBrain as a robust, reproducible and scalable platform for normative modelling of brain measures. Expected outcomes include harmonised neuroimaging datasets, validated normative models, individual-level centile and deviation outputs, documented computational pipelines, peer-reviewed manuscripts, conference presentations and open or shareable research tools where appropriate.
Requirements
- PhD or MD/PhD in artificial intelligence, data science, machine learning, biomedical engineering, computer science, computational neuroscience, neuroimaging, biostatistics or a closely related quantitative field.
- Strong formal training in artificial intelligence, data science and machine-learning methods.
- Demonstrated ability to apply advanced computational methods to large-scale biomedical, neuroscience or neuroimaging data.
- Strong quantitative and analytical skills, with the ability to develop, evaluate and interpret computational models.
- Ability to work independently and collaboratively within a multidisciplinary research environment involving neuroscience, psychiatry, engineering, data science and clinical research.
- Strong written and verbal communication skills, including the ability to communicate technical methods and findings to scientific collaborators.
Nice To Haves
- Experience with machine-learning methods.
- Experience with statistical modelling.
- Strong scientific programming skills.
- Experience developing and using reproducible computational workflows.
- Experience with neuroimaging data analysis is strongly preferred.
- Hands-on experience with MRI-based neuroimaging analysis, preferably including structural MRI, diffusion MRI, brain morphometry, connectivity measures or related imaging-derived phenotypes.
- Experience with large-scale or multi-site datasets.
- Experience with data harmonisation, normative modelling, artificial intelligence, high-performance computing, Git-based version control and reproducible research practices is highly desirable.
- Experience with common neuroimaging tools and standards, such as FreeSurfer, FSL, ANTs, BIDS, fMRIPrep, Nipype or related platforms, would be advantageous.
- A prior publication record in neuroimaging, computational neuroscience, data science, machine learning, artificial intelligence or biomedical engineering is preferred.
Responsibilities
- Work with large multi-site neuroimaging datasets.
- Follow institutional policies for data governance, privacy, human-subjects research and secure management of research data.
- Conduct preprocessing and quality control of neuroimaging data.
- Extract, harmonize and manage imaging-derived measures across datasets.
- Prepare and maintain data dictionaries and other project materials.
- Implement normative modelling, machine-learning and artificial intelligence pipelines.
- Conduct statistical analyses in relation to project aims.
- Prepare reproducible code, analytic workflows and clear technical documentation.
- Support collaborative analyses with internal and external research partners.
- Contribute to scientific manuscripts, conference presentations and grant reports.
Benefits
- Salary ranges that comply with the New York City Law on Salary Transparency in Job Advertisements
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
Education Level
Ph.D. or professional degree
