Bioinformatics Scientist (51675)

GAP SOLUTIONS INC•Durham, NC

2d•$110,000 - $128,000•Onsite

About The Position

The Bioinformatics Scientist will provide support to the National Institute of Environmental Health Sciences (NIEHS) within the National Institutes of Health (NIH). This position independently provides bioinformatics and data science support to advance the institute’s operational and research objectives. The role requires expertise in statistical genomics, machine learning, and scalable analysis and integration of high-dimensional omics data, applying AI-driven methods to generate biologically meaningful insights.

Requirements

Master's degree in Bioinformatics, Computational Biology, Genomics, Data Science, Biostatistics, Computer Science, Biomedical, Engineering, or a closely related quantitative field
3 years of experience
Demonstrated training or experience in machine learning, artificial intelligence, or advanced statistical modeling applied to high-dimensional biological data
Experience with R, Python, MATLAB, Linux, Unix, Java, Shell, PERL, Bash, SAS, HPC, Git, Docker, Singularity, Apptainer, and Workflow management
Skilled in Next gen sequencing data analysis: Bulk RNA-Sequencing, Next gen sequencing data analysis, Genome-wide association studies, and Single Cell RNA-Sequencing
Skilled working with large data sets, Microarray data analysis, Pipeline development, Multi-omics Analysis, and Machine Learning
Skilled with Core facility, Cloud platforms, Reproducible research practices, Data visualization, Representation learning for omics data
Skilled in Machine Learning, Deep Learning, and Multi-omics integration using deep learning

Nice To Haves

Ph.D. in Bioinformatics, Biostatistics, Computational Biology, or Biological/Life Sciences or similar.
Ability to communicate effectively, orally and in writing, with non-technical and technical staff
Detail-oriented and possess strong organizational skills with the ability to prioritize multiple tasks and projects

Responsibilities

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 data.
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 building 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 platforms
Perform computational analysis of, and interpret results.
Provide reports based on analysis of scientific data.
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.
Work independently with research groups to develop, implement, and refine analytical pipeline for high throughput genomics, transcriptomic, epigenetic, proteomics, digital spatial and other omics data.
Apply machine learning approach to analyze and integrate large-scale, complex multi-omic data to identify biological insights.
Collaborate with scientists to design, analyze, manage and interpret all types of data.
Design and execute computational experiments.
Work with staff on planning of experiments, and data analysis for internal and collaborative projects; use bioinformatics expertise to advise and help bench scientists on experimental design and trouble-shooting.
Work with staff to develop specifications for new analysis; design, test and implement solutions.
Make recommendations to investigators about the correct computational tools for testing scientific hypotheses and reaching valid conclusions.
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; organize and edit content of meeting reports.
Prepare scientific reports and progress reports; assemble data to prepare tables, graphs and slides; conduct scientific and program related information searches and report results.
Organize daily laboratory notebook on experiments; prepare weekly updates on on-going experiments and tasks; provide monthly progress notes on assigned projects; submit final progress reports and future directions on projects.
Organize laboratory notebook or computer database to record results of calculations.
Share results at lab meetings.
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 data analysis with existing computational and statistical methods.
Assist in evaluating and interpreting results for validity and scientific meaning.
Establish and maintain reproducible data analysis pipelines and standardized operating procedures (SOPs); develop comprehensive documentation to ensure methodologies are transparent, reproducible, and readily applicable to related studies.
Develop and implement robust analytical strategies for the integration of multi-omic datasets generated internally, as well as relevant publicly available datasets, to enable comprehensive and biologically meaningful interpretation.
Create novel programs and algorithms that facilitate discovery of knowledge in investigating large and complex data.
Develop and optimize programs and scripts that facilitate organization, integration and data-mining of large data sets; 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 pipe-lines for data.
Participate in research design with investigators for determining best practices pertaining to the bioinformatics analysis in new and ongoing projects.
Visualize and interpret data to create reports and presentations for scientific audiences.
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 in the 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.
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 computational analysis of data.
Provide ad hoc trainings and hands-on workshops on the use of bioinformatics tools.
Provide training of students, new investigators, and other laboratory personnel in the use of techniques, procedures and equipment to complete the objectives of the laboratory.
Onboard and train staff involved in new clinical trials, including the import of a wide variety of legacy data set; provide rigorous quality control of these data.
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 US and abroad.
Work with staff, collaborate with outside researchers, and contribute to positive overall teamwork; teach Bioinformatics principles and methodologies.
Collaborate with biologists, statisticians and/or other bioinformaticians in the design of models summarizing/explaining experimental data.
Attend group meetings; present findings; author publications resulting from projects.
Present analysis results at research conferences and meetings.
Present new research data in group settings, at meetings or seminars.
Conduct analyses on NextGen sequencing data including data derived in ChIP-Seq,RNA-Seq, miRNA-Seq and other experimental models
Conduct analysis and interpretation on data from genomic platforms including expression, exon, tiling, promoter and others array types
Conduct data analysis and interpretation on other large data types in genomic context
Establish and maintain work flows including experimental design, analyses of data quality, genome and meta-genome integration and others
Write utility scripts, macros andor custom programs or algorithms in support of biological discovery
Coordinate with biologists andor other bioinformaticians in the design of models summarizing and explaining experimental data; provide interpretive analyses of dataderived from different experimental platforms to generate biological meaning
Prepare reports and publication quality graphics summarizing experimental data including providing written documents
Participate in meetings with biologists; present findings to individuals and groups
Develop work products and documentation related to applying advanced computational and data analysis approaches to generate biological insights.
Independently design analytical strategies; identify and resolve scientific or technical challenges; design studies; analyze and interpret high-throughput biological data; and prepare and present results.
Develop work products and documentation supporting integrative analysis of internally generated datasets.
Contribute to manuscript preparation by drafting data analysis sections, creating publication-quality figures, and facilitating data submission to appropriate external repositories.
Develop and maintain custom analytical software, scripts, and computational pipelines.
Evaluate and implement commercial and open-source tools as appropriate; lead pipeline design and development efforts; establish reproducible workflows and standard operating procedures (SOPs); and provide comprehensive methodological documentation.
Develop and optimize analytical pipelines for multi omics data.
Identify, evaluate, and implement appropriate computational methods for preprocessing, quality control, integration, clustering, differential expression, and downstream analysis of single-cell datasets.
Provide ad hoc training sessions and hands-on workshops on bioinformatics tools and analytical methodologies.
Participate in group meetings; present analytical findings; and maintain current knowledge of emerging technologies and advances in biology, statistics, computer science, and bioinformatics.