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)
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.
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 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)
Preferred Qualifications
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:
1) Curriculum vitae 2) Brief cover letter describing research interests and relevant experience 3) Contact information for 2–3 references
Function
Research Support
Scheduled Weekly Hours:
40
Saint Louis University is an equal opportunity/affirmative action employer. All qualified candidates will receive consideration for the position applied for without regard to race, color, religion, sex, age, national origin, disability, marital status, sexual orientation, military/veteran status, gender identity, or other non-merit factors. If accommodations are needed for completing the application and/or with the interviewing process, please contact Human Resources at 314-977-5847.
