Bioinformatics Scientist

Requirements

• Next gen sequencing data analysis: Bulk RNA-Sequencing
• Next gen sequencing data analysis
• Genome-wide association studies
• Single Cell RNA-Sequencing
• Work with large data sets
• Microarray data analysis
• Pipeline development
• Multi-omics Analysis
• Machine Learning
• Core facility
• Cloud platforms
• Reproducible research practices
• Data visualization
• Representation learning for omics data
• Machine learning and Deep learning
• Multi-omics integration using deep learning
• Deliverables:
• 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. - Ad-Hoc
• 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. - Ad-Hoc
• 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. - Ad-Hoc
• 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. - Ad-Hoc
• 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. - Ad-Hoc
• Statement of Work Details:
• Collaborate with scientists to design, analyze, manage and interpret all types of data. - 1
• Work with an interdisciplinary team to apply computational data analysis approaches to make biological discoveries. - 2
• Conduct analyses on NextGen sequencing data including data derived in ChIP-Seq,RNA-Seq, miRNA-Seq and other experimental models. - 3
• Conduct analysis and interpretation on data from genomic platforms including expression, exon, tiling, promoter and others array types. - 4
• Work independently with research groups to develop, implement, and refine analyt

Benefits

Additional Information

(ID: 2026-2420) Axle is a bioscience and information technology company that offers advancements in translational research, biomedical informatics, and data science applications to research centers and healthcare organizations nationally and abroad. With experts in biomedical science, software engineering, and program management, we focus on developing and applying research tools and techniques to empower decision-making and accelerate research discoveries. We work with some of the top research organizations and facilities in the country including multiple institutes at the National Institutes of Health (NIH). Axle is seeking a Bioinformatics Scientist to join our vibrant team at the National Institutes of Health (NIH) supporting the Research Triangle Park, NC. Benefits We Offer: 100% Medical, Dental & Vision Coverage for Employees Paid Time Off and Paid Holidays 401K match up to 5% Educational Benefits for Career Growth Employee Referral Bonus Flexible Spending Accounts: Healthcare (FSA) Parking Reimbursement Account (PRK) Dependent Care Assistant Program (DCAP) Transportation Reimbursement Account (TRN) Position Information: 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. Additional Qualifications: Certifications & Licenses Three years of experience - Ph.D. in Bioinformatics, Biostatistics, Computational Biology or a biological/life science Ph.D. preferred (or Master's) in Bioinformatics, Computational Biology, Genomics, Data Science, Biostatistics, Computer Science, Biomedical Engineering, or a closely related quantitative field. Demonstrated training or experience in machine learning, artificial intelligence, or advanced statistical modeling applied to high-dimensional biological data. Field of Study Mathematics and Computer Science Biology Environmental Science Genetics Molecular Biology Software R Python MATLAB Linux Unix Java Shell PERL Bash SAS Bash / Linux / HPC Git Docker / Singularity / Apptainer Workflow management

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