Mathematical Modeler

The African Population and Health Research Center (APHRC) is a leading Africa-based, African-led, international research institution headquartered in Nairobi, Kenya. APHRC conducts policy-relevant research on population, health, education, urbanization and related development issues in sub-Saharan Africa.

APHRC seeks to recruit a Mathematical Modeler to work in the Data Science and Evaluation (DSE) Theme within the Research Division.

Duties/Responsibilities

The Mathematical Modeler will be responsible for creating models that demonstrate complex processes for solving health-related problems. They will leverage existing data resources within and beyond APHRC and use their skills combined with software technology to support effective health decision making.

The Mathematical Modeler will:

• Develop and adapt/modify existing mathematical models including deterministic, stochastic, network and individual or agent-based models for health outcomes;
• Work closely with DSE data scientists and AI software developers/engineer to design efficient programs, algorithms, or systems to reduce programming time for parameter sampling, model fitting (to data), and analyses;
• Import and export large sets of raw and synthetic data files for use in statistical analysis and machine learning;
• Manipulate, transform, encrypt, and combine data from multiple data sets including data at the APHRC micro portal, INSPIRE platform and other administrative data sources;
• Perform analytical (counterfactual) simulation exercises using mathematical models for various health outcomes at APHRC;
• Perform literature reviews supported by domain experts, researchers and epidemiologists, to identify model parameters;
• Perform descriptive and exploratory statistical analysis of individual-level or aggregate-level data to parameterize transmission models;
• Validate code and models to ensure algorithms are complete, reproducible, accurate and of high quality prior to analysis;
• Maintain high quality coding practices, version control, and documentation of coding for reproducibility;
• Develop standard operating procedures for effective mathematical modeling activities at DSE;
• Communicate and liaise with research, policy, program, and community partners including coordinating and chairing collaborator meetings;
• Contribute to report and manuscript writing, knowledge translation products, grants, and ethics review board applications;
• Prepare tables, figures, and reports for end-users, including clinicians, researchers, community-based organizations, public health decision-makers;
• Train, mentor, and DSE staff interested in mathematical modeling; and
• Work with internal and international collaborators on modelling projects.

Qualifications, Skills, and Experience

• Master’s degree in Mathematical Epidemiology, Applied Mathematics, Epidemiology, Statistics, Computer Science or other related field. Holders of Bachelor’s degrees with relevant experience will also be considered.
• At least three years’ relevant experience in modelling systems and/or numerical methods.
• Experience in mathematical dynamic modelling of infectious disease transmission, PK modelling, Non-linear models or agent-based models.
• Experience with economic analyses / economic evaluations / health-economics is an asset.
• Must be fully proficient in the use of R, Python.
• Ability to manage computer programming activities and support analytic operations.
• Experience in Frequentist and Bayesian statistics, and likelihoods.
• Experience with machine-learning and data visualization tools.
• Experience in basic statistical analysis, modelling or scientific computing.
• Good communication skills to describe findings to both technical and non-technical audiences.
• Excellent problem-solving skills, has attention to detail and a strong analytical mind.
• Demonstrates ability to work both independently and to work collaboratively with internal and external team members, and stakeholders.
• Ability to multi-task, work accurately and effectively to deadlines; has good self-assessment of timing of tasks and ability to set deadlines. Organizational and time management skills to manage and prioritize workload.
• Demonstrate an appreciation of technical and analytic challenges, and learning new approaches and topics.

This position is classified under Nationally Recruited Positions (NRP), Grade V in our scales.