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# Bioinformatics Analyst

- **Company:** Albert Einstein College of Medicine
- **Location:** New York, NY, United States
- **Experience:** Experienced
- **Contract:** Temporary contract
- **Skills:** Bioinformatics, Computational Biology, Computer Simulation, Computer Programming, R (Programming Language), Python (Programming Language), MATLAB, Machine Learning, High Performance Computing, Parallel Computation, Cobra, Information Technology, Feature Selection, Machine Learning Operations, Software Version Control
- **Published:** September 15, 2026
- **Apply:** https://www.jofdav.com/jobs/59719860-bioinformatics-analyst

## About the Role

* Bachelor's or Master's degree in Bioinformatics, Computational Biology, Biomedical Engineering, Computer Science, Applied Mathematics, or a related quantitative discipline, and at least 2 years of computational research experience after graduation.
 * Strong programming experience in Python, MATLAB, and R.
 * Experience developing reproducible computational analysis pipelines.
 * Experience working in Linux/Unix environments and with version control systems.
 * Familiarity with high-performance computing environments, workflow automation, and parallel computing.
 * Excellent written and verbal scientific communication skills.
 * Ability to work largely independently but with periodic guidance from PI and more senior lab members., * Experience analyzing next-generation sequencing data, particularly RNA-seq.
 * Familiarity with metabolomics, proteomics, lipidomics, or other multi-omics datasets.
 * Experience applying machine learning methods to biological data.
 * Experience with genome-scale metabolic modeling, constraint-based modeling, COBRA Toolbox/COBRApy, or related systems biology methods.
 * Prior experience contributing to collaborative biomedical research and scientific publications., This is a full-time, grant-funded appointment expected to last one to two years, contingent upon continued funding. Successful performance is expected to result in substantial contributions to multiple collaborative projects and co-authorship on peer-reviewed publications. The position also offers excellent experience for individuals interested in pursuing graduate study or careers in computational biology, bioinformatics, systems biology, or biomedical data science.

## Description

* Implement, document, and maintain standardized computational pipelines for analysis of multi-omics datasets, with particular emphasis on bulk RNA-seq and integration with proteomic, metabolomic, and lipidomic data.
 * Build computational workflows based on genome-scale metabolic network models for identifying metabolic biomarkers, context-specific metabolic model reconstruction, and performing constraint-based flux analyses to generate mechanistic hypotheses.
 * Apply established machine learning workflows for multi-omics integration, including feature selection, phenotype classification, latent network inference, and survival prediction using methods such as random forests, mixed graphical models, and related statistical learning techniques.
 * Adapt computational pipelines for efficient execution on a high-performance computing (HPC) environment, including workflow automation and parallel computing.
 * Apply these computational methods to collaborative studies investigating metabolic adaptations across multiple disease models, including diabetes, cancer dormancy, immune cell development, and neurodegenerative disease.
 * Interpret computational results through collaboration with experimental scientists to generate biologically meaningful and experimentally testable hypotheses.
 * Contribute to dissemination of methods and results through manuscripts and presentations.


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