AIMS 2026

Internships

AIMS 2026

Internships

AIMS 2026

Internships

Cooperative Masters in Mathematical Epidemiology

Whether you’re studying disease trends, strengthening health surveillance, or developing data-driven health technologies, AIMS Mathematical Epidemiology interns help translate health data into actionable understanding. Trained in disease modeling, statistical epidemiology, and computational analysis, they bring the tools needed to analyze outbreaks, evaluate interventions, and support better public health decisions.

Overview

Training Experts in Disease Modeling and Health Analytics

The Cooperative Master’s in Mathematical Epidemiology at AIMS Cameroon prepares students to apply mathematics, statistics, and computational modeling to public health challenges. The program focuses on understanding how diseases spread, how interventions affect outbreaks, and how data-driven models can guide health policy and technology development. Students receive advanced training in mathematical modeling, statistical epidemiology, computational simulation, and data analysis, enabling them to study infectious diseases and other health dynamics with scientific rigor. Courses are taught by internationally recognized researchers and experts in epidemiology, mathematics, and public health. As a result, students gain state-of-the-art training aligned with global research and health innovation efforts.

Overview

Training Experts in Disease Modeling and Health Analytics

The Cooperative Master’s in Mathematical Epidemiology at AIMS Cameroon prepares students to apply mathematics, statistics, and computational modeling to public health challenges. The program focuses on understanding how diseases spread, how interventions affect outbreaks, and how data-driven models can guide health policy and technology development. Students receive advanced training in mathematical modeling, statistical epidemiology, computational simulation, and data analysis, enabling them to study infectious diseases and other health dynamics with scientific rigor. Courses are taught by internationally recognized researchers and experts in epidemiology, mathematics, and public health. As a result, students gain state-of-the-art training aligned with global research and health innovation efforts.

Overview

Training Experts in Disease Modeling and Health Analytics

The Cooperative Master’s in Mathematical Epidemiology at AIMS Cameroon prepares students to apply mathematics, statistics, and computational modeling to public health challenges. The program focuses on understanding how diseases spread, how interventions affect outbreaks, and how data-driven models can guide health policy and technology development. Students receive advanced training in mathematical modeling, statistical epidemiology, computational simulation, and data analysis, enabling them to study infectious diseases and other health dynamics with scientific rigor. Courses are taught by internationally recognized researchers and experts in epidemiology, mathematics, and public health. As a result, students gain state-of-the-art training aligned with global research and health innovation efforts.

Courses on the Program

The program includes training in areas such as:

  • Dr. Woldegebriel Assefa

    York University, Canada

    Introduction to concepts in Mathematical Modelling

  • Dr. Osman Chaibu

    University of Health and Allied Sciences, Ghana

    Developing Mathematical Models in the context of Public Health

  • Prof. Eustarckio Kazonga

    University of Zambia

    Epidemiology for Disease Modelling

  • Prof. Thierry Chekouo

    The University of Minnesota Twin Cities,USA

    Advanced Data Analysis

  • Dr. Fazil Baksh

    University of Reading, UK

    Supervised Machine Learning

  • Prof. JC Loredo-Osti

    Memorial University, Canada

    Stochastic Modelling of Infectious Diseases

  • Dr. David Jaurès FOTSA

    University of Bertoua, Cameroon

    Numerical Methods

  • Prof. Ziad Taib

    Atlas Biostat, Sweden

    Bayesian Statistics

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Our Students Can Help!

Organizations hosting interns from this program gain access to talent trained to analyze and model complex public health challenges.

During their internships, students typically work on analytical projects that support research institutions, health organizations, government agencies, and health technology companies.

1

Disease modeling and outbreak analysis.

Our interns support organizations building mathematical models to understand disease spread and evaluate interventions.

2

Health data analysis.

They can analyze epidemiological datasets to identify trends and risk factors.

3

Public health forecasting.

Supporting decision-makers with predictive models for disease dynamics.

4

Health technology development.

Contributing to digital tools for surveillance, monitoring, and response systems.

5

Evidence-based policy support

Producing analytical reports that inform public health strategies.

Why It Works

The strength of the program lies in the combination of world-class academic training and structured industry engagement.

Rigorous Training with Global Expertise

The Mathematical Epidemiology program combines rigorous mathematical training with real-world health applications. Students are taught by visiting faculty from leading universities and research centers worldwide, exposing them to the latest research methods and analytical tools in epidemiology and public health modeling. This international academic environment ensures that graduates are trained to a standard comparable to top programs globally.

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Rigorous Training with Global Expertise

The Mathematical Epidemiology program combines rigorous mathematical training with real-world health applications. Students are taught by visiting faculty from leading universities and research centers worldwide, exposing them to the latest research methods and analytical tools in epidemiology and public health modeling. This international academic environment ensures that graduates are trained to a standard comparable to top programs globally.

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Applied Public Health Impact for Partners.

At the same time, the cooperative structure connects students with organizations working directly on health challenges—allowing them to apply their training in practical contexts. For partners, this means access to interns capable of contributing to data-driven public health solutions.

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Applied Public Health Impact for Partners.

At the same time, the cooperative structure connects students with organizations working directly on health challenges—allowing them to apply their training in practical contexts. For partners, this means access to interns capable of contributing to data-driven public health solutions.

Get Started

Building Africa’s Next Generation of Experts.

For students, it ensures that their academic training directly supports real-world impact. Together, these elements make the program a powerful pathway for developing the next generation of African experts in epidemiology, health analytics, and disease modeling.

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Building Africa’s Next Generation of Experts.

For students, it ensures that their academic training directly supports real-world impact. Together, these elements make the program a powerful pathway for developing the next generation of African experts in epidemiology, health analytics, and disease modeling.

Get Started