Remote Senior Bioinformatics Scientist Jobs

Bioinformatics Scientist

Position Closes: 06.29.2026

National Institutes of Health / National Institute of Environmental Health Sciences (NIEHS)

RJIT Solutions is an information technology and bioscience company that specializes in providing innovative solutions in biomedical research and data science. We serve healthcare organizations by leveraging the expertise of our team in science, software engineering, and program/project management. Our commitment to excellence has made us a trusted partner of top research organizations, including multiple institutes at the National Institutes of Health (NIH). At RJIT Solutions, we combine the agility of a small business with the comprehensive capabilities of a large organization to accelerate research and enhance decision-making processes in healthcare and research sectors. As part of our unrelenting focus on quality and compliance, RJIT Solutions’ delivery is based on Certified Matured Processes including CMMI L3 SVC, ISO 20000, ISO 27001, and ISO 9001 quality processes.

Place of Performance: NIEHS, 111 T.W. Alexander Dr., Bldg. 101, Room A031, Research Triangle Park, NC 27709

Position Summary and Objectives:

This position will independently provide bioinformatics support to advance the institute’s research programs, with a primary focus on single cell and spatial omics data analysis. The role requires advanced proficiency in statistical modeling, machine learning, and integrative analysis to extract biologically meaningful insights from complex cellular systems. The Bioinformatics Scientist will collaborate closely with investigators and multidisciplinary teams to design analytical strategies, ensure data quality, interpret results, and translate findings into actionable scientific conclusions.

Technical Requirements: Bioinformatics Scientist

Programming and troubleshooting support for the dissemination of research data

• Generate and optimize programs and scripts for the analysis of data; create programs and algorithms and develop computational infrastructure resources for organizing and parsing data from large and complex datasets.
• Serve as bioinformatics expert and coordinate with teams of biologists to conduct experimental queries and/or perform portions of studies using complex procedures and techniques common to modern bioinformatics.
• Coordinate the building of bioinformatics infrastructure to ensure easy and meaningful scientific analysis and interpretation of data.
• Provide broad-based programming and analytic support for a wide variety of bioinformatic and research projects.
• Install, troubleshoot, and run open-source and commercial scientific software on relevant platforms.

Computation on research data

• Work independently with research groups to develop, implement, and refine analytical pipelines for single cell data analysis.
• Analyze and integrate large-scale, complex multi-omic data to identify biological insights.
• Identify, evaluate, and implement different analytical approaches for processing scRNA-seq data across experimental protocols, and investigate visualization tools for single cell datasets.
• Perform computational analysis of, and interpret, results.
• Perform sequencing and alignment of raw data, and interpret new data using larger public-access datasets.
• Provide interpretive analyses of data derived from different experimental platforms to generate biological meaning.
• Write custom programs and algorithms to support data analyses and discovery, and provide reports based on analysis of scientific data.

Scientific programming and experimental design with staff

• Collaborate with scientists to design, analyze, manage, and interpret all types of data.
• Design and execute computational experiments.
• Work with staff on the planning of experiments and data analysis for internal and collaborative projects; use bioinformatics expertise to advise and assist bench scientists on experimental design and troubleshooting.
• Work with staff to develop specifications for new analyses; design, test, and implement solutions.
• Make recommendations to investigators about the correct computational tools for testing scientific hypotheses and reaching valid conclusions.

Documentation and reporting of results at laboratory meetings

• Prepare scientific and progress reports; assemble data to prepare tables, graphs, and slides; conduct scientific and program-related information searches and report results.
• Organize the daily laboratory notebook on experiments; prepare weekly updates on ongoing experiments and tasks; provide monthly progress notes on assigned projects; and submit final progress reports and future directions on projects.
• Maintain proper and detailed documentation of the analysis performed and report results at lab meetings.
• Attend scientific and programming meetings; take and compile comprehensive notes; and organize and edit the content of meeting reports.

Statistical support and analysis on research data

• Devise novel methods of statistical analysis for collected data.
• Utilize and adapt existing bioinformatics techniques to check for trends and patterns in the data.
• Perform data processing and analysis with existing computational and statistical methods.
• Assist in evaluating and interpreting results for validity and scientific meaning.
• Establish reproducible data analysis pipelines and standard operating procedures; provide detailed documentation of methodologies so they can be reproduced and applied to similar studies.
• Develop analytical approaches to integrate multiple omic datasets generated internally as well as publicly available datasets.

Research and service goals in the context of the laboratory’s overall mission

• Create novel programs and algorithms that facilitate the discovery of knowledge from large and complex data.
• Develop and optimize programs and scripts that facilitate the organization, integration, and data-mining of large datasets; integrate these models into a framework of best practices.
• Participate in the design of new protocols involving computational methods.
• Work with staff on the development and maintenance of bioinformatics tools, scripts, and pipelines for data.
• Participate in research design with investigators to determine best practices for bioinformatics analysis in new and ongoing projects.
• Collaborate with experimental teams to guide study design and validate new assay methods.
• Visualize and interpret data to create reports and presentations for scientific audiences.

Evaluation of new experimental approaches and protocols

• Research and review literature to retrieve targeted clinical or scientific information, including novel statistical methods, from publicly available resources.
• Collaborate with staff to review current and historical procedures for the acquisition, quality control, and management of data.
• Analyze and evaluate data cleaning and harmonization needs using a variety of descriptive statistics and analytic methods.
• Identify new tools and resources for reaching biologically meaningful conclusions.
• Collaborate with experimentalists and computational biologists to develop new computational tools to answer research questions of interest.

Training of personnel in scientific, statistical, and programmatic software

• Provide training in and technical support (including product updates and version control) for programs, algorithms, archives, and pipelines generated during the course of this work.
• Instruct staff in the computational analysis of data, and provide ad hoc trainings and hands-on workshops on the use of bioinformatics tools.
• Train students, new investigators, and other laboratory personnel in the techniques, procedures, and equipment required to meet the objectives of the laboratory.
• Onboard and train staff involved in new clinical trials, including the import of a wide variety of legacy datasets, and provide rigorous quality control of these data.

Interdisciplinary collaboration with other research centers

• Work with an interdisciplinary team to apply computational data analysis approaches to make biological discoveries.
• Collaborate with group members in experiments associated with data collection.
• Interact with all levels of staff and communicate with outside collaborators in the U.S. and abroad; contribute to positive overall teamwork and teach bioinformatics principles and methodologies.
• Collaborate with biologists, statisticians, and other bioinformaticians in the design of models summarizing and explaining experimental data.

Scientific dissemination

• Deliver at least one presentation per year to audiences outside the Government; attend group meetings, present findings, and author publications resulting from projects.

Other

• Conduct analyses on next-generation sequencing data, including ChIP-Seq, RNA-Seq, miRNA-Seq, and other experimental models.
• Conduct analysis and interpretation of data from genomic platforms, including expression, exon, tiling, promoter, and other array types.
• Conduct data analysis and interpretation of other large data types in a genomic context.
• Establish and maintain workflows, including experimental design, analysis of data quality, and genome and meta-genome integration.
• Write utility scripts, macros, and/or custom programs or algorithms in support of biological discovery.
• Prepare reports and publication-quality graphics summarizing experimental data, including written documentation.

Specific Qualifications:

• Master’s degree required in Bioinformatics, Biostatistics, Computational Biology, or a biological/life science; a Ph.D. in one of these disciplines is preferred.
• A minimum of three (3) years of relevant experience.
• Relevant fields of study include Mathematics and Computer Science, Biology, Environmental Science, Genetics, and Molecular Biology.
• Demonstrated expertise in single cell analysis (scRNA-seq, scATAC-seq, scMultiomics) and spatial transcriptomics; specialized training or certification in single cell analysis is preferred.
• History of reproducible, well-documented analytical work and a record of scientific contribution appropriate to the level of the position.

Required Software and Tools:

• Programming and analysis environments: R, Python, MATLAB, Java, Perl, Shell, Bash, and SAS.
• Operating systems and computing platforms: Linux, Unix, high-performance computing (HPC), and cloud computing.
• Bioinformatics frameworks and libraries: Bioconductor and Seurat / Scanpy.

Required Skills and Expertise:

• Next-generation sequencing data analysis, including bulk RNA-Sequencing and single cell RNA-Sequencing.
• Single cell analysis (scRNA-seq, scATAC-seq, scMultiomics) and spatial transcriptomics data analysis.
• Multi-omics analysis and integration.
• Genome-wide association studies and microarray data analysis.
• Pipeline development, reproducible analysis, and common workflow language.
• Machine learning applied to large, complex biological datasets.
• Experience working with large datasets and supporting a core facility environment.

Other Requirements:

• Telework may be authorized if approved by the Task Leader, COR, and the Contracting Officer.