Overview
The Research Associate will support AfriClimate AI’s applied research portfolio by contributing to the development, fine-tuning, and validation of AI-driven climate and weather modelling tools. Working closely with the research team, the successful candidate will play a hands-on role in data preparation, model development and evaluation, ensuring that research outputs are robust, open and relevant for African contexts.
Research & Development
- Assist in designing, implementing, and testing AI-based climate and weather forecasting methodologies.
- Preprocess and manage large geospatial datasets (e.g., observational data, satellite products, reanalysis datasets).
- Support the development of benchmarking frameworks for model evaluation, including skill scores, bias correction and uncertainty quantification.
- Contribute to the setup and maintenance of MLOps pipelines for training, deployment and monitoring of AI models.
- Collaborate with team members on documentation, and reproducibility of workflows.
Collaboration & Knowledge Sharing
Work with meteorological agencies, universities and international partners on joint research tasks.Contribute to open-source datasets, code repositories and technical documentation.Support the preparation of research outputs, including peer-reviewed articles, technical reports, and policy briefs.Present results in internal and external meetings (workshops and conferences).Essential Qualifications & Experience
Master’s degree in Climate Science, Meteorology, Machine Learning or a related field.Proficiency in Python.Experience working with geospatial and gridded datasets (e.g., ERA5, CHIRPS, CMIP, satellite-based products).Knowledge of machine learning methods applied to climate or weather problems.Familiarity with standard model evaluation metrics and statistical analysis.Ability to work independently as well as collaboratively in distributed teams.Ability to communication technical work clearly.Desirable Skills & Experience
Previous research experience on African climate datasets and / or data-sparse contexts.Hands-on experience with deep learning frameworks (e.g., PyTorch, TensorFlow).Exposure to MLOps tools (e.g., MLflow, Docker, Kubernetes, Airflow).Familiarity with cloud computing (AWS, GCP, Azure) or HPC workflows.Knowledge of numerical weather prediction (NWP) systems, downscaling, or data assimilation.Experience contributing to open-source projects or collaborative codebases.AfriClimate AI
AfriClimate AI is a grassroots research organisation advancing climate resilience in Africa through open, community-driven AI research. We focus on developing region-specific datasets, tools, and methodologies to bridge the gap between global models and local needs, supporting equitable and actionable climate solutions across the continent.
Mission-driven impact : Contribute to climate resilience and equity across Africa through open, locally grounded research.Flexible, remote-first work : Collaborate with an international network while working from anywhere in Africa.Open science ethos : Work in a fully open-source, community-driven environment that values transparency, reproducibility, and shared ownership.Professional growth : Access mentorship, attend leading conferences, and shape the future of climate AI research in the Global South.Collaborative culture : Join a multidisciplinary, values-aligned team working at the intersection of science, technology, and social impact.Travel opportunities : Participate in key events, workshops, and field collaborations across Africa and beyond.Competitive compensation : Receive a salary package that reflects your expertise, with flexibility for different levels of experience and location.#J-18808-Ljbffr
