Master's Degree with 3 years of related experience or a PhD in bioinformatics, epidemiology, public health, or a related field.
Proven ability using computational tools for HIV transmission cluster detection through genetic sequence data analysis.
Experience in developing and maintaining bioinformatics pipelines specific to HIV or infectious diseases in various settings.
Strong knowledge of phylogenetic and phylodynamic methods, with hands-on experience in interpreting molecular epidemiology data.
Collaborative experience working with diverse teams, translating scientific needs into practical analytic solutions.
Responsibilities
Serve as the expert for HIV sequence analysis and related methods, ensuring practices align with current standards.
Review and approve changes to analytic methods and workflows for scientific accuracy and compliance.
Validate outputs and software enhancements through rigorous testing and quality assurance.
Develop comprehensive strategies for synthetic and validation datasets, covering a range of scenarios.
Evaluate sequence data quality and pipeline performance, recommending improvements as necessary.
Advise on the modernization and optimization of bioinformatics workflows to enhance analytic capabilities.
Benefits
Opportunity to contribute to cutting-edge research in HIV surveillance and public health.
Collaborative work environment with a multidisciplinary team.
Support for continuous professional development and training in bioinformatics and epidemiology.
Engagement with the latest technologies and methodologies in bioinformatics.
Full Job Description
As the Bioinformatics/Phylogenetics Specialist, you will provide expertise in HIV sequence analysis, pairwise genetic distance methods, phylogenetics/phylodynamics, cluster detection logic, sequence data quality, analytic validation, and scientific testing. You will review changes that affect analytic methods, validate scientific outputs, support synthetic and test data strategy, and advise on modernization of bioinformatics pipelines. This role will be under TSPi, Abt Global's subsidiary that provides digital services and solutions.
This role is contingent upon project award.
Core Responsibilities
Serve as the expert for HIV sequence analysis, pairwise genetic distance methods, phylogenetics, and phylodynamics, providing scientific guidance to ensure analytic approaches align with current HIV surveillance and research best practices.
Review, assess, and approve proposed changes to analytic methods, cluster detection logic, and bioinformatics workflows, ensuring scientific accuracy, reproducibility, and regulatory compliance.
Validate analytic outputs, algorithms, and software enhancements through rigorous scientific testing, benchmarking, and quality assurance activities to maintain the integrity and reliability of cluster identification results.
Develop and oversee strategies for synthetic, test, and validation datasets, ensuring comprehensive coverage of real-world use cases, edge cases, and performance testing scenarios.
Evaluate sequence data quality and analytic performance, identifying potential issues related to data integrity, method assumptions, or pipeline execution and recommending corrective actions as needed.
Advise on the modernization, optimization, and scalability of bioinformatics pipelines and computational workflows, supporting the adoption of emerging methods, technologies, and best practices to improve analytic capabilities and operational efficiency.
What We Value
Master's Degree + 3 years of relevant experience or a PhD.
Degrees in bioinformatics, epidemiology, public health, or a related field are required.
Experience using computational tools to identify potential HIV transmission clusters by analyzing genetic sequence data.
Experience developing, validating, and maintaining bioinformatics pipelines for the analysis of HIV or other infectious disease sequence data in research, surveillance, or public health environments.
Demonstrated knowledge of phylogenetic and phylodynamic methods, including interpretation of transmission cluster analyses, molecular epidemiology findings, and genetic distance-based approaches.
Experience collaborating with multidisciplinary teams of epidemiologists, software developers, data scientists, and public health stakeholders to translate scientific requirements into analytic solutions and system enhancements.
