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Position Overview
The Vanderbilt ALS Research Center (VARC) is seeking an enthusiastic and highly motivated Postdoctoral Computational Biologist to join our Multi-Omics and Informatics for Neurodegenerative Disease (MIND) team. The successful candidate will analyze and integrate multi-omics datasets from existing and newly generated cohorts to define the molecular architecture of ALS and related neurodegenerative diseases, with the goal of identifying biomarkers, therapeutic targets, and disease subgroups with translational relevance.
This position offers access to unique unpublished patient-derived datasets, including postmortem tissues, biofluids, and cell-based disease models. The candidate will work in a highly collaborative, interdisciplinary environment that values rigor, complementarity, innovation, mentorship, and open science.
Key Responsibilities
- Develop and implement reproducible pipelines for the analysis and integration of genomic, epigenomic, transcriptomic, proteomic, single-cell/single-nucleus, and spatial omics datasets.
- Apply systems biology, network biology, statistical modeling, and/or artificial intelligence approaches to identify molecular signatures associated with ALS risk, progression, patient stratification, and therapeutic target discovery.
- Maintain well-documented, reproducible workflows using best practices in data management, code versioning, and computational research transparency.
- Collaborate closely with clinicians, wet-lab scientists, computational biologists, and trainees across multidisciplinary projects.
- Communicate analytical approaches and findings clearly to both computational and non-computational audiences.
- Contribute to manuscript preparation, grant applications, scientific presentations, and mentoring of undergraduate and graduate students.
Required Qualifications
- PhD in Computational Biology, Bioinformatics, Biomedical Informatics, Systems Biology, Biostatistics, Genetics, Neuroscience, or a related quantitative discipline.
- Demonstrated experience analyzing large-scale omics datasets.
- Strong programming skills in R and/or Python, with experience in bash scripting.
- Experience working in high-performance computing and/or cloud-based environments.
- Familiarity with biological databases and resources relevant to omics analysis, such as ENCODE, GTEx, or related platforms.
- Strong written and verbal communication skills.
- Ability to work both independently and collaboratively in a multidisciplinary research environment.
Preferred Qualifications
- Prior experience in ALS, FTD, or other neurodegenerative disease research.
- Experience with single-cell or single-nucleus RNA-seq, ATAC-seq, spatial transcriptomics, epigenomics, proteomics, or long-read sequencing data.
- Experience with multi-omics integration, network analysis, biomarker discovery, or patient stratification approaches.
- Familiarity with machine learning or deep learning methods applied to biomedical datasets.
- Interest in translational research and the development of computational tools or biomarkers with clinical relevance.
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