Senior Research Scientist

We are seeking a highly motivated and skilled Data Scientist to join our research team in the Department of Neurology. This role is focused on advancing our understanding of aging and neurodegenerative diseases through data-driven analyses. The successful candidate will be responsible for analyzing complex biomedical data sets, applying machine learning techniques, and working closely with multidisciplinary teams to uncover patterns, trends, and relationships in aging data.

Required Qualifications: (as evidenced by an attached resume)

● Ph.D. degree in Data Science, Computer Science, Bioinformatics, Biomedical Engineering, Computational Biology, Neuroscience, or a closely related field.

● 5 years of experience (strong expertise) in data analysis and machine learning, with proficiency in Python, R, or similar programming languages.

● Experience working with large biomedical datasets (e.g., genomics, clinical records, neuroimaging, etc.).

● Solid understanding of statistical analysis and experimental design.

● Previous experience or a strong interest in aging research, neurodegenerative diseases (such as Alzheimer's, Parkinson’s, or dementia), or neuroscience.

● Experience with data visualization tools (e.g., Tableau, D3.js, matplotlib, ggplot2) and the ability to create clear and informative visualizations.

Preferred Qualifications:

● Experience with multi-omics data analysis (e.g., genomics, transcriptomics, proteomics).

● Familiarity with neuroimaging data analysis tools (e.g., FSL, SPM, or FreeSurfer).

● Knowledge of aging-related biomarkers and aging research methodologies.

● Familiarity with high-performance computing and cloud computing tools (e.g., AWS, Google Cloud) is a plus.

Key Responsibilities:

● Collaborate with researchers, clinicians, and experts in aging and neurodegenerative diseases to design and implement data analysis strategies.

● Analyze large-scale, complex data sets (including genomic, imaging, and clinical data) to identify trends, biomarkers, and insights related to aging and neurological health.

● Apply advanced statistical and machine learning techniques (e.g., predictive modeling, clustering, dimensionality reduction) to extract meaningful insights from multi-modal data.

● Develop and implement algorithms to process, clean, and transform large datasets to support research objectives.

● Conduct exploratory data analysis, hypothesis testing, and develop data-driven recommendations for ongoing research projects.

● Create and maintain reproducible workflows for data analysis and visualization using tools such as MATLAB, Python and R.

Collaborate with the team to integrate genetic and genomic data with clinical and imaging data to improve disease modeling.

● Present findings in meetings and contribute to scientific publications, conference presentations, and grant applications.

● Stay up-to-date with current advancements in aging research, neuroscience, data science, and machine learning techniques.

Special Notes:

The Research Foundation of SUNY is a private educational corporation. Employment is subject to the Research Foundation policies and procedures, sponsor guidelines and the availability of funding. FLSA Exempt position, not eligible for the overtime provisions of the FLSA. Minimum salary threshold must be met to maintain FLSA exemption.

Visit The Office of Postdoctoral Affairs to learn more about our postdoctoral community.

Resume/CV and cover letter should be included with the online application.

Stony Brook University is committed to excellence in diversity and the creation of an inclusive learning, and working environment. All qualified applicants will receive consideration for employment without regard to race, color, national origin, religion, sex, pregnancy, familial status, sexual orientation, gender identity or expression, age, disability, genetic information, veteran status and all other protected classes under federal or state laws.

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The starting salary range (or hiring range) to be offered for this position is noted below, it represents SBU’s good faith and reasonable estimate of the range of possible compensation at the time of posting.

Schedule: Full-time

Shift: Day Shift