Aga Khan University Hospitals in Karachi, Pakistan and Nairobi, Kenya are private, not-for-profit institutions providing high quality health care. The Main Hospitals serve as the principal sites for clinical training for the University's Medical Colleges and Schools of Nursing and Midwifery in Pakistan and East Africa. Our Vision of Aga Khan University Hospital, Nairobi is to be the premier, tertiary, teaching and referral health care facility in sub-Saharan Africa. ​For over fifty years, Aga Khan University Hospital, Nairobi (AKUH) has been taking care of families in East Africa. As a private, not-for-profit hospital, we strive to provide access to quality healthcare to all who need it. At AKUH, patients are our first priority. Our team of medical professionals, faculty and staff are here to provide you and your loved ones with the highest standards of healthcare. We are committed to working together to ensure that you and your family receive outstanding medical services, first-rate facilities and compassionate care. The Aga Khan University Hospital, Nairobi has set the standard for comprehensive healthcare and modern medical education in East Africa. Our dedicated staff, advanced facilities and state-of-the-art technologies have earned the hospital great reputation as a leading medical institution and teaching hospital in the region, and beyond. Patients benefit from our unique team-based approach to car​e, which enables you to benefit from the diverse expertise of our entire team of medical professionals. As the teaching hospital for Aga Khan University’s Medical College and School of Nursing and Midwifery, we practice an evidence-based approach to medicine, driven by the cutting-edge research conducted by our experienced faculty members. Our approach to care is guided by our core principles of Quality, Access, Impact and Relevance.​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