The primary purpose of NGS Bioinformatics Developer is to develop, implement, and maintain computational pipelines and software tools for the analysis of Next Generation Sequencing (NGS) data for clinical molecular diagnostics laboratory. This would include working closely with a multidisciplinary team of molecular diagnostics scientists, bioinformaticians, pathologists, and software developers to support various genomics testing applications. This role requires strong expertise in bioinformatic... more details
**The ideal candidate will have experience developing and implementing computational pipelines and software tools for NGS data**
MISSION STATEMENT The mission of The University of Texas M. D. Anderson Cancer Center is to eliminate cancer in Texas, the nation, and the world through outstanding programs that integrate patient care, research and prevention, and through education for undergraduate and graduate students, trainees, professionals, employees and the public.
SUMMARY The primary purpose of NGS Bioinformatics Developer is to develop, implement, and maintain computational pipelines and software tools for the analysis of Next Generation Sequencing (NGS) data for clinical molecular diagnostics laboratory. This would include working closely with a multidisciplinary team of molecular diagnostics scientists, bioinformaticians, pathologists, and software developers to support various genomics testing applications. This role requires strong expertise in bioinformatics algorithms and data analysis techniques, and the ability to adapt to evolving technologies and clinical applications.
JOB SPECIFIC COMPETENCIES Develop bioinformatics pipelines. Develop and optimize bioinformatics pipelines for clinical molecular diagnostics laboratory. This would include processing and analyzing next generation sequencing (NGS) and other genomic data, including tasks such as quality control, alignment, variant calling, and annotation. This involves staying up-to-date with the latest tools and methods in the field and integrating them into existing pipelines to ensure accurate and efficient analysis.
Design and implement bioinformatic algorithms. Design and implement algorithms and statistical methods for the interpretation of genomic data, including identification of genetic variants, differential expression analysis, and pathway analysis. This requires a deep understanding of both bioinformatics theory and practical applications to derive meaningful insights from complex genomic datasets.
Develop RNA-seq pipelines for transcriptomic analyses. Develop specialized RNA-seq pipelines tailored for transcriptomic analysis, including preprocessing steps such as adapter trimming, read alignment to reference genomes or transcriptomes, quantification of gene and isoform expression levels, and differential expression analysis. This involves integrating specialized tools such as HISAT2, STAR, Salmon, or Kallisto into comprehensive workflows optimized for specific experimental designs and biological questions.
Implement bioinformatics pipelines for various NGS applications such as whole genome sequencing (WGS), exome sequencing (WES), targeted sequencing, single-cell sequencing, liquid biopsy analysis, and minimal residual disease (MRD) detection. This includes adapting existing pipelines and developing new methodologies to address the specific requirements and challenges associated with each application.
Gather input from stakeholders. Collaborate with molecular diagnostics professionals to understand project requirements, propose solutions, and provide technical support for data analysis and interpretation. This involves actively engaging with project teams to translate biological questions into computational workflows and troubleshooting issues that arise during data analysis.
Integrate existing bioinformatics tools and databases into custom workflows to address specific clinical application needs and improve analysis efficiency. This includes evaluating the suitability of available tools and databases for particular analyses and developing scripts or wrappers to automate data processing tasks and facilitate reproducibility. Maintain documentation and version control for developed software and pipelines, ensuring reproducibility and transparency of analyses. This includes writing comprehensive documentation for code and pipelines, managing code repositories using version control systems such as Git, and adhering to best practices for software development and data management.
Stay informed about new developments in bioinformatics tools, algorithms, and genomic databases, and evaluate their potential applicability to ongoing projects. This involves actively monitoring scientific literature, attending conferences, and participating in online forums and community discussions to identify emerging trends and technologies relevant to genomics research.
Participate in team meetings, seminars, and training sessions to share knowledge and best practices in bioinformatics analysis. This includes presenting updates on ongoing projects, leading discussions on relevant topics in bioinformatics, and providing training to team members on new tools and methods.
Provide support and training to other team members, including laboratory staff, precision oncology scientists, bioinformaticians, pathologists and clinical oncologists, on the use of bioinformatics tools and data analysis techniques. This involves offering guidance on experimental design, data preprocessing, and interpretation of results, as well as troubleshooting issues and answering technical questions to facilitate productive collaborations across disciplines
Bachelor's degree in Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Science, Engineering, Computer Science, Statistics, Computational Biology, or related field. Three years experience in scientific software development/analysis. With Master's degree, one years experience required. With PhD, no experience required. It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state or local laws unless such distinction is required by law. http://www.mdanderson.org/about-us/legal-and-policy/legal-statements/eeo-affirmative-action.html
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