أخصائي معلوماتية حيوية أول

Overview

M42 is a global health champion powered by artificial intelligence (AI), technology and genomics to advance innovation in health for people and the planet. Headquartered in Abu Dhabi, M42 combines its specialized, state-of-the-art facilities with integrated health solutions like genomics and biobanks, and harnesses advanced technologies to deliver precise, preventive and predictive care, to disrupt traditional healthcare models and positively impact lives globally.

The Senior Bioinformatician will join a large genomics and bioinformatics team supporting the Emirati Genome Program (EGP), a national-scale whole genome sequencing initiative. The role is responsible for leading the development, optimization, and automation of large-scale genomic data processing workflows, ensuring reliable, scalable, and reproducible analysis across diverse sequencing technologies. The position contributes to the advancement of production genomics capabilities through workflow innovation, cloud-based computing solutions, quality control frameworks, and continuous improvement of bioinformatics infrastructure.

Responsibilities

• Design, develop, implement, and maintain scalable bioinformatics pipelines and workflows for large-scale genomic data processing.
• Build and optimize automated workflows for sequencing quality control, alignment, variant calling, annotation, and downstream genomic analyses.
• Develop and manage workflow orchestration platforms such as Nextflow and equivalent workflow management systems.
• Improve workflow scalability, reproducibility, monitoring, performance, and reliability across high-volume sequencing datasets.
• Evaluate, benchmark, and integrate new bioinformatics tools, sequencing technologies, and analytical approaches into production environments.
• Troubleshoot workflow failures, performance bottlenecks, data quality issues, and unexpected analytical results.
• Support harmonization of genomic data across sequencing platforms, software versions, pipelines, callers, and data releases.
• Apply best practices in genomic quality control, including assessment of sequencing metrics, sample integrity, contamination, variant quality, batch effects, and cohort release criteria.
• Contribute to cloud-based genomic computing environments, containerization technologies, workload optimization, and reproducible software deployment practices.
• Collaborate with scientists, bioinformaticians, software engineers, platform teams, cloud specialists, and data management teams to deliver technical and scientific objectives.
• Identify opportunities for automation, standardization, and continuous improvement of production genomics workflows and operational processes.
• Ensure compliance with organizational policies, data governance requirements, confidentiality standards, and applicable regulatory frameworks.
• Document workflows, technical processes, and validation activities to support reproducibility and operational excellence.

Qualifications

• PhD in Bioinformatics, Computational Biology, Genomics, Computer Science, Data Science, Engineering, or a related field.
• Equivalent combination of advanced education and relevant professional experience may be considered.

• Significant experience in production bioinformatics, genomic computing, workflow development, cloud genomics, or related technical fields.
• Demonstrated experience leading large-scale genomics infrastructure, pipeline development, or workflow automation projects.
• Experience working with whole genome sequencing (WGS) datasets and large-scale genomic analysis environments.
• Experience with cloud platforms, workflow orchestration frameworks, and high-performance computing environments is strongly preferred.
• Scientific publications, open-source contributions, or ownership of large-scale genomics systems are advantageous.

• Strong programming skills in Python, shell scripting, or related languages.
• Advanced Linux command-line proficiency.
• Experience with Nextflow or similar workflow orchestration frameworks.
• Knowledge of genomic processing tools such as DRAGEN, Sentieon, GATK, bcftools, samtools, and related technologies.
• Experience with Docker, Singularity/Apptainer, containerized workflows, and reproducible software environments.
• Strong understanding of genomic file formats including FASTQ, BAM/CRAM, VCF, and gVCF.
• Expertise in genomic quality control, variant calling, structural variation analysis, and large-scale genomic data processing.
• Familiarity with Git, software version control, and workflow testing practices.
• Strong analytical, problem-solving, communication, and stakeholder management skills.
• Ability to work independently while collaborating effectively within multidisciplinary technical and scientific teams.

• Design, develop, implement, and maintain scalable bioinformatics pipelines and workflows for large-scale genomic data processing.
• Build and optimize automated workflows for sequencing quality control, alignment, variant calling, annotation, and downstream genomic analyses.
• Develop and manage workflow orchestration platforms such as Nextflow and equivalent workflow management systems.
• Improve workflow scalability, reproducibility, monitoring, performance, and reliability across high-volume sequencing datasets.
• Evaluate, benchmark, and integrate new bioinformatics tools, sequencing technologies, and analytical approaches into production environments.
• Troubleshoot workflow failures, performance bottlenecks, data quality issues, and unexpected analytical results.
• Support harmonization of genomic data across sequencing platforms, software versions, pipelines, callers, and data releases.
• Apply best practices in genomic quality control, including assessment of sequencing metrics, sample integrity, contamination, variant quality, batch effects, and cohort release criteria.
• Contribute to cloud-based genomic computing environments, containerization technologies, workload optimization, and reproducible software deployment practices.
• Collaborate with scientists, bioinformaticians, software engineers, platform teams, cloud specialists, and data management teams to deliver technical and scientific objectives.
• Identify opportunities for automation, standardization, and continuous improvement of production genomics workflows and operational processes.
• Ensure compliance with organizational policies, data governance requirements, confidentiality standards, and applicable regulatory frameworks.
• Document workflows, technical processes, and validation activities to support reproducibility and operational excellence.

• PhD in Bioinformatics, Computational Biology, Genomics, Computer Science, Data Science, Engineering, or a related field.
• Equivalent combination of advanced education and relevant professional experience may be considered.

• Significant experience in production bioinformatics, genomic computing, workflow development, cloud genomics, or related technical fields.
• Demonstrated experience leading large-scale genomics infrastructure, pipeline development, or workflow automation projects.
• Experience working with whole genome sequencing (WGS) datasets and large-scale genomic analysis environments.
• Experience with cloud platforms, workflow orchestration frameworks, and high-performance computing environments is strongly preferred.
• Scientific publications, open-source contributions, or ownership of large-scale genomics systems are advantageous.

• Strong programming skills in Python, shell scripting, or related languages.
• Advanced Linux command-line proficiency.
• Experience with Nextflow or similar workflow orchestration frameworks.
• Knowledge of genomic processing tools such as DRAGEN, Sentieon, GATK, bcftools, samtools, and related technologies.
• Experience with Docker, Singularity/Apptainer, containerized workflows, and reproducible software environments.
• Strong understanding of genomic file formats including FASTQ, BAM/CRAM, VCF, and gVCF.
• Expertise in genomic quality control, variant calling, structural variation analysis, and large-scale genomic data processing.
• Familiarity with Git, software version control, and workflow testing practices.
• Strong analytical, problem-solving, communication, and stakeholder management skills.
• Ability to work independently while collaborating effectively within multidisciplinary technical and scientific teams.