Postdoctoral Fellow
Position Overview
We are seeking a highly motivated Postdoctoral Fellow with a PhD in Computational Biology, Bioinformatics, Biostatistics, Data Science, or a related quantitative field to join an interdisciplinary research program focused on Alzheimers disease (AD) and neurodegeneration.
The fellow will lead and contribute to advanced bioinformatics, multi-omics integration, and statistical modeling efforts using large, well-phenotyped longitudinal datasets (e.g., proteomics, transcriptomics, imaging, clinical, and biomarker data). The position is ideal for a candidate interested in mechanistic discovery, biomarker development, and translational neuroscience, with opportunities for high-impact publications and grant development.
Key Responsibilities
- Perform computational analysis of large-scale omics datasets, including proteomics, transcriptomics, and related modalities
- Integrate multi-omics data with clinical, cognitive, and imaging phenotypes in longitudinal cohorts
- Develop and apply statistical and machine-learning models (e.g., mixed-effects models, survival analysis, dimensionality reduction, clustering, trajectory modeling)
- Lead reproducible analysis pipelines in R, Python, or related frameworks
- Interpret results in biological and clinical context, with emphasis on Alzheimers disease mechanisms and biomarkers
- Prepare figures, tables, and methods for peer-reviewed manuscripts and conference presentations
- Collaborate with clinicians, wet-lab scientists, and biostatisticians in an interdisciplinary environment
- Contribute to grant proposals and progress reports as appropriate
- Mentor graduate or undergraduate trainees in computational methods (optional, depending on interest)
Required Qualifications
- PhD in Computational Biology, Bioinformatics, Biostatistics, Data Science, Systems Biology, or a related quantitative discipline
- Strong experience with high-dimensional biological data analysis
- Proficiency in R and/or Python for statistical computing and data analysis
- Solid foundation in statistics and data modeling, particularly for longitudinal or cohort-based data
- Demonstrated ability to work independently and manage complex datasets
- Strong written and verbal communication skills in English
- Evidence of productivity (e.g., peer-reviewed publications, preprints, or advanced projects)
Preferred Qualifications
- Experience with longitudinal modeling (e.g., mixed-effects models, disease progression modeling)
- Familiarity with neurodegenerative disease research, Alzheimers disease, or aging biology
- Experience with proteomics platforms (e.g., Olink, SomaScan, mass spectrometry)
- Knowledge of multi-omics integration, network analysis, or pathway enrichment methods
- Experience working with large consortium datasets (e.g., ADNI, AMP-AD, UK Biobank, similar)
- Interest in translational research, biomarker discovery, or drug target identification
- Experience with reproducible research practices (version control, documentation, workflow tools)
Environment & Opportunities
The fellow will join a highly collaborative research environment at the interface of neurology, neuroscience, and computational biology, with access to rich datasets and strong clinical context. The position offers:
- Intellectual ownership of projects
- Opportunities for first-author publications
- Exposure to grant writing and translational research strategy
- Career mentorship tailored to academic, industry, or hybrid career paths
Term & Compensation
- One-year appointment with possibility of renewal based on funding and performance
- Competitive salary and benefits commensurate with experience and institutional guidelines
Application Instructions:
Applicants should submit:
1) Curriculum vitae 2) Brief cover letter describing research interests and relevant experience 3) Contact information for 2–3 references
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