Post Doctoral Fellow

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.

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.