Post Doctoral Fellow

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 Alzheimer's 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)

Requirements

• Experience with longitudinal modeling (e.g., mixed-effects models, disease progression modeling)
• Familiarity with neurodegenerative disease research, Alzheimer's 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:
• Curriculum vitae 2) Brief cover letter describing research interests and relevant experience 3) Contact information for 2-3 references
• Grant-funded Post-Doctoral appointments may be terminated if grant funding ends.
• This position does not currently sponsor J1, H1B, or O visas.
• Function
• Research Support
• Scheduled Weekly Hours:
• 40

Benefits

Additional Information

Who is Saint Louis University? Founded in 1818, Saint Louis University is one of the nation's oldest and most prestigious Catholic universities. SLU, which also has a campus in Madrid, Spain, is recognized for world-class academics, life-changing research, compassionate health care, and a strong commitment to faith and service. Postdoctoral Fellow - Computational Biology / Bioinformatics Focus: Multi-omics and Longitudinal Modeling in Alzheimer's Disease Appointment: Full-time, 1-year term (renewable pending funding and performance) 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 Alzheimer's 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.

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