Bioinformatics/Data Scientist

Nextonic Solutions LLC; Frederick (MD); On-site; USD 80,000 - 120,000; Full time

Job summary

A leading solutions provider is seeking a Bioinformatics/Data Scientist in Frederick, MD to analyze multi-omics data from organoid models. This role is key in developing computational frameworks for organoid quality assessment and requires a PhD in a recognized quantitative field. Candidates should have extensive experience with single-cell analysis, strong programming skills in R and Python, and familiarity with data visualization tools. The position involves collaboration with teams and the integration of various datasets.

Qualifications

• Extensive experience with single-cell data analysis.
• Strong programming skills in R and Python.
• Knowledge of proteomics and metabolomics workflows.

Responsibilities

• Analyze complex datasets including RNA sequencing and proteomics data.
• Develop and implement computational pipelines for data processing.
• Collaborate with experimental teams to interpret results.

Skills

Single-cell data analysis

Programming in R

Programming in Python

Statistical analysis

Data visualization

Education

PhD in bioinformatics, computational biology, biostatistics, or related field

Tools

Seurat

Scanpy

Job description

Frederick, United States | Posted on 01/09/2026

Nextonic Solutions is seeking a Bioinformatics/Data Scientist to join our vibrant team at the National Institutes of Health (NIH) supporting the Standardized Organoid Model Center in Frederick, MD. The Standardized Organoid Model Center is an NIH-funded initiative dedicated to advancing organoid research through the development of validated, reproducible, and well-characterized organoid models. The center brings together interdisciplinary teams of researchers to establish standardized protocols, develop quality control measures, and create resources that will benefit the broader organoid research community.

Overview

The Bioinformatics/Data Scientist will conduct comprehensive analyses of multi-omics data generated from organoid systems and corresponding normal tissues. This position is central to the SOM Center's research objectives, focusing on characterizing organoid fidelity, identifying biomarkers of successful differentiation, and developing computational frameworks for organoid quality assessment.

Responsibilities

• The successful candidate will analyze complex datasets including single-cell RNA sequencing, bulk RNA sequencing, proteomics, and metabolomics data from various organoid systems and their tissue counterparts.
  
• The position will develop and implement computational pipelines for data processing, quality control, and statistical analysis.
  
• A major component of the role involves integrating SOM-generated data with publicly available datasets to benchmark organoid characteristics against normal tissue profiles.
  
• The position requires close collaboration with experimental teams to interpret results and guide protocol optimization, as well as contributing to manuscript preparation and presenting findings at scientific conferences.
  

Qualifications

• Candidates must hold a PhD in bioinformatics, computational biology, biostatistics, or a related quantitative field.
  
• Extensive experience with single-cell data analysis, including familiarity with tools such as Seurat, Scanpy, or similar platforms, is essential.
  
• Strong programming skills in R and Python are required, along with experience in statistical analysis and data visualization.
  
• Knowledge of proteomics and metabolomics data analysis workflows is necessary.
  

Preferred Qualifications

• Previous experience analyzing organoid datasets is strongly preferred.
  
• Experience with machine learning approaches for biological data, familiarity with pathway analysis tools, and knowledge of developmental biology principles will be considered valuable assets.
  
• Experience with high-performance computing environments and version control systems is desirable.