In 2021, we were awarded a grant by the Global South AI4COVID Program titled "End-to-end AI and data systems for targeted surveillance and management of COVID-19 and future pandemics affecting Uganda (COAST). The Modeling and forecasting workstream which is part of the project is tasked to build statistical and mathematical forecasting models to aid in real-time tracking of COVID-19 spread and associated risks so as to inform regional and population specific interventions. The workstream also aims to evaluate government responses to mitigate the epidemic. We wish to recruit a junior modeler who will work with the senior modeler to achieve the objects of the modelling workstream and those of the overall COAST project.

The primary role of this position will be to work on developing and calibrating statistical and mathematical / simulation models for COVID-19 projections and developing figures and data visualization approaches from simulations. The position will focus on time series models (e.g., ARIMA, ETS and dynamical models), generalized linear models, compartmental and stochastic mathematical models for COVID-19. Responsibilities include coding mathematical models (preferably in R/Rstudio software), reading in data and writing outputs, writing model fitting algorithms, and running model simulations using R/Rstudio and developing dashboards.

The Junior Data Modeler position requires a deep understanding of probability distributions; compartmental, stochastic and dynamical systems modeling; and reproducible data science in general. The position involves self-directed learning and a desire to learn new approaches relevant to research questions, and a motivation to help make mathematical modeling a transparent and inclusive process with knowledge-users.

- Develop and adapt/modify mathematical models of COVID-19 transmission: deterministic, stochastic.
- Importing and exporting large sets of raw and synthetic data files for use in statistical analysis and modelling.
- Manipulate, transform and merge data from multiple data sets
- Perform literature reviews supported by information specialists and epidemiologists, to identify model parameters
- Perform descriptive and exploratory statistical analysis of individual-level or aggregate-level data to parameterize transmission models
- Perform model fitting (parameter estimation) for mathematical models
- Prepare tables, figures, and reports for end-users, including researchers, community-based organizations, public health decision-makers
- Validation of 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
- Efficiently identify and correct syntax and programming logic errors in all code.
- Contribute to report and manuscript writing and other knowledge translation products
- Development of data visualization dashboards
- Build predictive and statistical forecasting models and evaluating modelling predictions.

**Knowledge, skills and abilities:**

- Data management and wrangling/pre-processing such as cleaning, structuring, transformation, merging, identifying extreme values (outliers), identifying gaps in data (missing values) and associated imputation approaches.
- Knowledge of Statistical data analysis including graphical presentations of data, programming, data processing, statistical and mathematical modelling with R software.
- Report writing and presentation
- Time series analysis
- Mathematical and statistical modelling including conceptualization, creation and analysis of mathematical and statistical models
- Data science and big data analysis
- Experience in at least one programming language especially R software

**Qualification requirements:**

- At least an undergraduate degree in a numerate or analytical discipline such as statistics, mathematics, data science, mathematical epidemiology, epidemiology, ecology or related discipline
- Strong statistics and mathematical background
- Relevant experience in mathematical modeling of infectious disease transmission especially COVID-19 is not required but is an added advantage.
- Proficient in R programming.
- Experience in Frequentist and Bayesian statistics, and likelihoods
- Experience with machine-learning and data visualization an asset

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More Details

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JDMX001

Kampala

Full-time

Head Data and Modelling Work Stream head

JDMX001

Kampala

Full-time

Head Data and Modelling Work Stream head

JDMX001

Kampala

Full-time

Head Data and Modelling Work Stream head

Kampala

Full-time

Head Data and Modelling Work Stream head

In 2021, we were awarded a grant by the Global South AI4COVID Program titled "End-to-end AI and data systems for targeted surveillance and management of COVID-19 and future pandemics affecting Uganda (COAST). The Modeling and forecasting workstream which is part of the project is tasked to build statistical and mathematical forecasting models to aid in real-time tracking of COVID-19 spread and associated risks so as to inform regional and population specific interventions. The workstream also aims to evaluate government responses to mitigate the epidemic. We wish to recruit a junior modeler who will work with the senior modeler to achieve the objects of the modelling workstream and those of the overall COAST project.

The primary role of this position will be to work on developing and calibrating statistical and mathematical / simulation models for COVID-19 projections and developing figures and data visualization approaches from simulations. The position will focus on time series models (e.g., ARIMA, ETS and dynamical models), generalized linear models, compartmental and stochastic mathematical models for COVID-19. Responsibilities include coding mathematical models (preferably in R/Rstudio software), reading in data and writing outputs, writing model fitting algorithms, and running model simulations using R/Rstudio and developing dashboards.

The Junior Data Modeler position requires a deep understanding of probability distributions; compartmental, stochastic and dynamical systems modeling; and reproducible data science in general. The position involves self-directed learning and a desire to learn new approaches relevant to research questions, and a motivation to help make mathematical modeling a transparent and inclusive process with knowledge-users.

- Develop and adapt/modify mathematical models of COVID-19 transmission: deterministic, stochastic.
- Importing and exporting large sets of raw and synthetic data files for use in statistical analysis and modelling.
- Manipulate, transform and merge data from multiple data sets
- Perform literature reviews supported by information specialists and epidemiologists, to identify model parameters
- Perform descriptive and exploratory statistical analysis of individual-level or aggregate-level data to parameterize transmission models
- Perform model fitting (parameter estimation) for mathematical models
- Prepare tables, figures, and reports for end-users, including researchers, community-based organizations, public health decision-makers
- Validation of 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
- Efficiently identify and correct syntax and programming logic errors in all code.
- Contribute to report and manuscript writing and other knowledge translation products
- Development of data visualization dashboards
- Build predictive and statistical forecasting models and evaluating modelling predictions.

**Knowledge, skills and abilities:**

- Data management and wrangling/pre-processing such as cleaning, structuring, transformation, merging, identifying extreme values (outliers), identifying gaps in data (missing values) and associated imputation approaches.
- Knowledge of Statistical data analysis including graphical presentations of data, programming, data processing, statistical and mathematical modelling with R software.
- Report writing and presentation
- Time series analysis
- Mathematical and statistical modelling including conceptualization, creation and analysis of mathematical and statistical models
- Data science and big data analysis
- Experience in at least one programming language especially R software

**Qualification requirements:**

- At least an undergraduate degree in a numerate or analytical discipline such as statistics, mathematics, data science, mathematical epidemiology, epidemiology, ecology or related discipline
- Strong statistics and mathematical background
- Relevant experience in mathematical modeling of infectious disease transmission especially COVID-19 is not required but is an added advantage.
- Proficient in R programming.
- Experience in Frequentist and Bayesian statistics, and likelihoods
- Experience with machine-learning and data visualization an asset

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