Key responsibilities
The Post Doc will have sufficient knowledge on vector-borne diseases, infectious disease modelling, and applied computing to enable him/her to lead the development of robust prediction models that balances the need for simplicity and accuracy. Despite this expectation, the post doc will have opportunities to develop his/her skills further through training, mentorship or any other relevant competency development activities. The Post Doc will work in a multidisciplinary team of local and international researchers, and s/he will:
set up research questions and analytical frameworks that will guide the development of dynamic models for studying transmission patterns of the vector-borne zoonotic diseases that have been prioritised for this work. The analytical frameworks will be developed in consultation with local and international partners and stakeholders
develop process-based spatially explicit vector-host-pathogen mathematical or simulation models and link these with decision support frameworks where policy-relevant outputs such as dynamic risk maps are displayed
apply statistical and computational methods to available primary and secondary data to generate input parameters for the dynamic models that will have been developed
participate in webinars, conferences, journal clubs and stakeholder meetings where s/he will be expected to share research findings, lessons learnt, or new research leads based on the work s/he will be leading
develop new research proposals in partnership with the project team members to extend the work s/he will be leading be given adequate opportunities to enrol for professional trainings to build their competencies on modelling and data science
Requirements
A doctoral degree in epidemiology, applied statistics or public health in the previous 5 years from an accredited college or university
PhD candidates who are at the final stages of their program (e.g. awaiting graduation) will also be considered
Strong quantitative skills including statistical, systems dynamic, and simulation modelling
Strong programming skills using the commonly used languages e.g. R, Python.
A track record of publications. Higher weights will be allocated to publications where the candidate is the first author
Excellent knowledge of the English language both in speaking and in writing.
Experience on training and mentoring students, junior scientists or project partners
Supervising the design and implementation of research projects