Summary
M42’s Biogenix Labs is an omics center focused on genomic and molecular technologies for precision medicine. The Variant Scientist analyzes and classifies germline and somatic variants, interprets scientific literature, and prepares clinical genetic reports. The role also includes quality control, variant and disease curation, assay and process improvements, and collaboration with bioinformatics and IT teams. Applicants need a PhD in a relevant field and at least five years of variant interpretation experience.
The posting
As published on m42.ae. Pulled from the employer's site and shown as they wrote it.
Overview
M42 delivers comprehensive healthcare services across the full continuum of care; from primary care to advanced specialty treatments. Leveraging cutting-edge health technologies and precision medicine, we ensure the highest standards of effectiveness, efficiency, and patient-centered outcomes. With a global presence spanning more than 480 facilities in 27 countries and a dedicated workforce of over 20,000 professionals, M42 is uniquely positioned to redefine the future of healthcare on a global scale.
Biogenix Labs, our Omics Center of Excellence, is a pioneering facility advancing precision medicine through cutting-edge genomic and molecular technologies. Specializing in Next-Generation Sequencing (NGS) and multi-omics research, the lab delivers deep insights into human health, disease, and treatment pathways. As part of M42’s Integrated Health Solutions platform, Biogenix Labs accelerates scientific discovery, supports national programs, and strengthens the UAE’s leadership in personalized healthcare.
As the Variant Scientist will work under supervision of the Clinical Geneticist to accurately analyze and classify germline and somatic variants from genomic sequencing data using in-house software and scientific literature to produce high-quality clinical reports.
Responsibilities
- Accurately classify germline and somatic variants for Whole Genome/Whole Exome Sequencing, and panel tests.
- Utilize a variety of in-house software tools to analyze clinical molecular data.
- Read and interpret scientific literature and curate relevant findings in a clear, concise, and precise manner.
- Summarize inherited and somatic genetic test results to generate high quality clinical reports.
- Perform critical quality control functions for molecular reports that complies with quality management programs and standard operating procedures.
- Support improvements for current assays and processes.
- Curate variants, genes, and diseases for scientific and clinical relevance.
- May train junior team members.
- Develop SOP for variant interpretation; maintain tracking documents in relation to the variant-scoring process.
- Collaborate with the Bioinformatician/IT regarding technology needs for new gene tests.
Qualifications
- Phd in Cancer Genetics, Human Genetics, or Biological Sciences.
- Minimum of 5 years of related experience in Variant Interpretation.
- Ability to research variants of unknown significance using literature searches with detailed annotation and integration of different data types in a timely fashion.
- Ability to use and understand external databases and tools such as COSMIC, TCGA, predictive Networks, ASIAN, SEBINI, CARRIE, and INSIGHT and prediction software such as polyphon, SIFT, Mutation Taster, ALAMUT, UCSC Genome Browser, Ensembl Genome Browser, NCBI BLAST.Restricted.
- Experience with DNA sequence analysis, next-generation sequencing (NGS) technologies, use of online database entire ecosystem of real-world evidence to deliver real-time, actionable.
- Excellent analytic skills.
- Excellent writing and communication skills, organization, and meticulousness.
- Understand experimental methods, data analysis methods and inferences that can be applied to both single-gene experimentation and high-throughput analyses.
- Understand large genomic datasets, and their computational analysis, integrating protein and genetic interaction data, regulatory data at the DNA, RNA, and protein levels, polymorphism and disease associated sequence variation data, quantitative phenotypic data and drug-target interaction data.
- Accurately classify germline and somatic variants for Whole Genome/Whole Exome Sequencing, and panel tests.
- Utilize a variety of in-house software tools to analyze clinical molecular data.
- Read and interpret scientific literature and curate relevant findings in a clear, concise, and precise manner.
- Summarize inherited and somatic genetic test results to generate high quality clinical reports.
- Perform critical quality control functions for molecular reports that complies with quality management programs and standard operating procedures.
- Support improvements for current assays and processes.
- Curate variants, genes, and diseases for scientific and clinical relevance.
- May train junior team members.
- Develop SOP for variant interpretation; maintain tracking documents in relation to the variant-scoring process.
- Collaborate with the Bioinformatician/IT regarding technology needs for new gene tests.
- Phd in Cancer Genetics, Human Genetics, or Biological Sciences.
- Minimum of 5 years of related experience in Variant Interpretation.
- Ability to research variants of unknown significance using literature searches with detailed annotation and integration of different data types in a timely fashion.
- Ability to use and understand external databases and tools such as COSMIC, TCGA, predictive Networks, ASIAN, SEBINI, CARRIE, and INSIGHT and prediction software such as polyphon, SIFT, Mutation Taster, ALAMUT, UCSC Genome Browser, Ensembl Genome Browser, NCBI BLAST.Restricted.
- Experience with DNA sequence analysis, next-generation sequencing (NGS) technologies, use of online database entire ecosystem of real-world evidence to deliver real-time, actionable.
- Excellent analytic skills.
- Excellent writing and communication skills, organization, and meticulousness.
- Understand experimental methods, data analysis methods and inferences that can be applied to both single-gene experimentation and high-throughput analyses.
- Understand large genomic datasets, and their computational analysis, integrating protein and genetic interaction data, regulatory data at the DNA, RNA, and protein levels, polymorphism and disease associated sequence variation data, quantitative phenotypic data and drug-target interaction data.