Clinical Bioinformatician, Cancer Centre at Aga Khan University

Nairobi, , Kenya -

Full Time

Start Date

Immediate

Expiry Date

09 Aug, 26

Salary

0.0

Posted On

11 May, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

NGS Data Analysis, Variant Calling, Variant Annotation, Python, R, Bash, Nextflow, Snakemake, GATK, VEP, ANNOVAR, Clinical Genomics, Human Genetics, ACMG Guidelines, Data Management, Bioinformatics Pipelines

Industry

Hospitals and Health Care

Description

Bio Informatician, NGS Department Genomic Medicine Entity Cancer Centre Location Nairobi, Kenya Introduction Chartered in 1983, Aga Khan University (AKU) is a private, autonomous, and self-governing international university, with 13 teaching sites in 6 countries over three continents. An integral part of the Aga Khan Development Network, AKU provides higher education in multiple health science and social science disciplines, carries out research pertinent primarily to low- and middle-income countries and operates 7 hospitals (soon 8) and over 325 outreach clinics, all at international standards. It has almost 2,500 students and 14,000 staff. The University is both a model of academic excellence and an agent of social change. As a leading international institution dedicated to excellence and change, AKU operates on the core principles of quality, relevance, impact, and access. Job Summary The Clinical Bioinformatician will be responsible for analyzing and interpreting high-throughput genomic data to support accurate diagnosis and improved understanding of rare genetic disorders and cancer. The role involves processing and quality control of Next Generation Sequencing (NGS) data, identifying clinically relevant variants, and collaborating closely with laboratory scientists, clinicians, and genetic counselors to deliver high-quality, actionable genomic insights that inform patient care and research. Responsibilities Genomic Data Analysis and Interpretation Process and analyze NGS data from germline and somatic sources (e.g., whole exome sequencing, targeted panels). Perform quality control, alignment, variant calling, annotation, and filtering of sequencing data. Interpret and classify genetic variants based on clinical relevance using established guidelines (e.g., ACMG/AMP). Clinical Reporting and Collaboration Collaborate with clinical laboratory scientists, physicians, and genetic counselors to review variant interpretations. Contribute to multidisciplinary discussions for patient case reviews. Participate with clinicians in preparing clinical reports that summarize genomic findings in a clear and actionable manner. Data Management, Tools, and Pipeline Optimization Maintain and enhance bioinformatics pipelines and databases used in variant analysis. Implement best practices for data management, version control, and documentation. Evaluate new bioinformatics tools and methods to improve analysis accuracy and efficiency. Research, Innovation, and Capacity Building Support research projects focused on rare genetic disorders and cancer genomics. Contribute to publications, presentations, and development of new analytical approaches. Provide training or mentorship to junior staff and students in genomic data analysis. Requirements Master’s degree in bioinformatics, Computational Biology, Genomics, Molecular Biology, or a related field. A PhD in a relevant discipline is an added advantage. Additional training or certification in clinical genomics, molecular diagnostics, or data science is desirable. Relevant Experience Minimum 2–3 years of experience in clinical or translational bioinformatics, ideally with NGS data analysis. Proficiency with bioinformatics tools and programming languages (e.g., Python, R, bash, workflow managers like Nextflow or Snakemake). Experience with standard variant annotation and filtering tools (e.g., VEP, ANNOVAR, GATK, bcftools, samtools). Strong working knowledge of human genetics, including Mendelian inheritance, variant pathogenicity, and cancer genomics. Familiarity with clinical variant classification guidelines (e.g., ACMG, AMP, CAP). Excellent analytical and problem-solving skills. Effective verbal and written communication skills to present results to non-technical audiences Personal Characteristics & Behaviours Analytical and Detail-Oriented: Demonstrates strong attention to accuracy and precision when handling complex genomic data and variant interpretations. Collaborative: Works effectively within interdisciplinary teams of clinicians, laboratory scientists, and researchers, fostering open communication and shared goals. Maintains the highest standards of integrity and confidentiality when handling sensitive patient genetic information. Organized and Accountable: Manages multiple analyses and reporting timelines efficiently while maintaining thorough documentation. Effective Communicator: Able to clearly explain complex genomic concepts to non-specialist audiences, including clinicians and administrators. Committed to continuous improvement and adherence to clinical laboratory standards and best practices

Responsibilities

The Clinical Bioinformatician analyzes and interprets high-throughput genomic data to support the diagnosis of cancer and rare genetic disorders. This includes processing NGS data, identifying clinically relevant variants, and collaborating with clinicians to deliver actionable genomic insights.