Duties And Responsibilities

As a Spatial Data Scientist, the candidate will work closely with other researchers on the project to develop and implement models for extrapolating both air pollution and heat exposures in space and time. Working in the context of a multidisciplinary team, the candidate will develop spatially intelligent algorithms for extrapolating exposures from sampled points to unmeasured locations in geographically diverse sub-Saharan African environments. This position involves repurposing large datasets from personal pollution and heat exposure monitors to derive exposure trends in space and time.

The successful candidate will:
-Utilise spatial data science (AI/ML) and statistical methods to derive environmental exposure (heat and air pollution) trends under varying exposure scenarios using a personal exposure dataset.
-Develop and implement algorithms for quantifying environmental exposure trends and extrapolating the same to unmeasured locations (based on sub-cohort measurements) bearing varying geographical characteristics.
-Collaborate with other researchers and stakeholders to understand project requirements and data processing workflows.
-Stay current with advancements in spatial data science and contribute to continuous improvement of model processes related to heat and pollution exposure characterization.
-Collaborate with the team to integrate spatial and temporal dimensions into overall data analysis strategies.
*NB: Midlands State University is an equal opportunities employer. In the interest of promoting gender parity, female candidates are encouraged to apply.