NAFASI ZA KAZI SENIOR RESEARCH SCIENTIST.

Responsibilities:

• To provide statistical expertise in development and implementation of spatiotemporal models to respond to a variety of malaria research questions related to risk estimations, estimating of morbidity and mortality, understanding transmission profiles, and optimizing the impact of interventions.
• To guide others and contribute to the best presentation of outputs from analysis, interpretation of results and relevant conclusions.
• Manage own academic research and administrative activities, including small-scale project management to coordinate multiple aspects of the work to meet deadlines.
• Lead collaboration and engagements with NMCPs to translate and communicate MAP’s modelling efforts, products, and outputs to foster utilization and uptake.
• Work with the data scientist and data engineering team on creating data-pipelines, setting up computation infrastructure and managing NMCP’s data and outputs requests.
• Work collaboratively with other scientists within the wider MAP group to produce estimates of malaria, acting as a source of information and advice to other members of the group.
• Apply due diligence by scrutinizing model results for all project deliverables, reviewing and refining theories as appropriate.
• Maintain rigorous data- and code management practices, including thorough documentation and version control, to ensure data replicability and cross-compatibility with past and future MAP products.
• Contribute ideas for new research projects and for generating research income.
• Contribute to and, as appropriate, lead, in the preparation of scientific reports and journal articles for publication of research findings from this work in open access journals.
• Present the research findings from this work at selected regional and international conferences and meetings.
• Travel to collaborators in different MECs, Europe, the United States, Africa, and Asia.
• Take reasonable care for your own safety and health and avoid harming the safety and health of others through any act or omission at work.
• Identify and assess workplace hazards and apply hazard controls.
• Report every workplace injury, illness or near miss, no matter how insignificant they seem.
• Abide by institutional policies and procedures.

Requirements:

• PhD in biostatistics, mathematics, or a similar quantitative discipline with epidemiological knowhow.
• Expertise in Bayesian modelling using Gaussian processes with demonstrable understanding of the issues arising from scaling these models to a global scale, validation, assessing performance and sensitivity analysis.
• Experience of multi-metric analysis and covariate selection in the context of modelling large and complex data with spatial correlations.
• Experience of state-of-the-art statistical software libraries such as INLA, TMB or similar packages.
• Demonstrable commitment to using best practices in writing code, including the use of source control, code documentation/repositories, and coding standards.
• Experience of working with national disease programmes, managing relationships with senior stakeholders, data-owners, and collaborators.
• Experience in research design and implementation, analyzing routine health data in LMICs hence good understanding of challenges on data utilization and quality issues in low resource settings.
• Ability to manage own academic research, mentoring junior staff, define and meet milestones on time.
• Demonstrable evidence of having worked successfully within a collaborative, team-based research setting.
• An understanding of the malaria epidemiology and public health surveillance.
• Track record of scientific publications in high quality peer-reviewed journals in the areas of epidemiology, modelling or health system research.
• Experience of working with NMCPs, understanding of malaria surveillance including using DHIS2.
• Knowledge and experience in working with ministries of health in LMICs, funding agencies and bilateral organizations.
• Experience in developing and delivering training for different audiences.
• Knowledge of other languages including Swahili, French, Spanish, Portuguese.
• Excellent communication skills (oral and written) in both professional and courteous manner.
• Proficiency in one or more programming languages (e.g., R/Python, Stata), knowledge of other statistical software and data visualization applications.

Application Process: