Research Data Analyst (Oncology)
Johns Hopkins University Baltimore, Maryland, United States · $49K–$86K/yr
Education Administration Programs · 2-10 employees
About the role
The Research Data Analyst will develop and maintain computational pipelines to analyze high-dimensional biomedical datasets, including single-cell, spatial, and genomic data. They will also generate publication-quality reports, models, and figures while contributing to manuscripts and grant applications.
What they look for
Requirements
Candidates must hold a bachelor's degree in a relevant field such as bioinformatics, computational biology, or data science, along with at least three years of related experience. Proficiency in programming languages like R or Python and experience with machine learning or biomedical data analysis are highly preferred.
Full description
The Sidiropoulos Laboratory at the Johns Hopkins University School of Medicine is seeking a highly motivated Research Data Analyst to support research in computational immunology and spatial multi-omics. The successful candidate will analyze high-dimensional multimodal biomedical datasets and maintain reproducible computational workflows. We are seeking a Research Data Analyst who will provide data analysis and related activities for various types of research projects and studies. The Research Data Analyst will contribute to ongoing development, maintenance, and use of a research data pipeline that collects and analyzes data.
Specific Duties & Responsibilities
- Collect data and generate reports and models.
- Run models, analyze model results, and prepare reports on the analysis.
- Conduct analyses in support of the assigned research project or study.
- Conduct statistical analyses using standard and statistical software packages.
- Design and prepare tables to illustrate analytic findings.
- Manage or contribute to entry of data in the assigned database.
- May engage in other research related responsibilities.
- Other duties as assigned.
In addition to the duties above:
- Develop and use reproducible pipelines for single-cell, spatial, genomic, immune-repertoire, imaging, and flow-cytometry analyses.
- Generate publication-quality figures, tables, reports, and presentations.
- Integrate experimental, molecular, spatial, and clinical data across projects.
- Contribute to manuscripts, abstracts, grant applications, and collaborative studies.
- Apply supervised and unsupervised machine-learning methods, including classification, regression, clustering, and dimensionality reduction.
- Support the use of deep-learning and biomedical foundation models for transcriptomic, spatial, imaging, or multimodal data.
- Maintain reproducible workflows using Git and environment-management tools.
- Support secure data transfer, storage, backup, and archiving.
- Participate in laboratory meetings, study design, troubleshooting, and interpretation.
Minimum Qualifications
- Bachelor’s degree in bioinformatics, computational biology, biostatistics, data science, computer science, biomedical engineering, biology, or a related field.
- Three years of related experience.
- Additional education may substitute for required experience and additional related experience may substitute for required education beyond a high school diploma/graduation equivalent, to the extent permitted by the JHU equivalency formula.
Preferred Qualifications
- Master’s degree in a relevant field or equivalent education and professional research experience.
- Experience with single-cell, spatial, genomic, immune-repertoire, imaging, flow-cytometry, or multi-omic data.
- Experience applying machine-learning, deep-learning, generative AI, or biomedical foundation models.
- Experience with high-performance computing, SLURM, GPUs, cloud computing, Docker, Singularity or Apptainer, Nextflow, or Snakemake.
- Familiarity with tools such as Seurat, Scanpy, Bioconductor, Git, Jupyter, R Markdown, or Quarto.
- Experience with cancer biology, immunology, molecular biology, or next-generation sequencing.
- Experience contributing to scientific manuscripts, presentations, or collaborative research projects.
- Experience analyzing biomedical, genomic, clinical, or other complex datasets.
- Programming experience in R, Python, or a comparable language.
Classified Title: Research Data Analyst Role/Level/Range: ACRP/04/MC Starting Salary Range: $49,200 - $86,200 Annually ($67,650 targeted; Commensurate w/exp.) Employee group: Full Time Schedule: Mon - Fri / 8a - 5:30p FLSA Status: Exempt Location: Hybrid/School of Medicine Campus Department name: SOM Onc Cancer Immunology/GI Clinical Re Personnel area: School of Medicine
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