Research Lead, AfriClimate AI
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Johannesburg, South Africa· Remote · 24 days agoDescription
The Research Lead will provide scientific and operational leadership for AfriClimate AI’s applied research portfolio, guiding the development, fine-tuning, and validation of AI-driven climate and weather modelling tools. The role involves coordinating a multidisciplinary team, collaborating with African and international partners, and ensuring research outputs are high-quality, open, and impactful.
Research Leadership & Delivery
The Research Lead will provide scientific and operational leadership for AfriClimate AI’s applied research portfolio, guiding the development, fine-tuning, and validation of AI-driven climate and weather modelling tools. The role involves coordinating a multidisciplinary team, collaborating with African and international partners, and ensuring research outputs are high-quality, open, and impactful.
Research Leadership & Delivery
- Lead the design, implementation, and evaluation of AI-powered, localised climate and weather forecasting methodologies.
- Support the integration of observational data, satellite products, and global reanalysis datasets with AI-based and statistical models.
- Develop benchmarking frameworks for model performance, including bias correction and uncertainty quantification.
- Implement and manage MLOps pipelines for training, deployment, monitoring, and updating AI models in production environments.
- Coordinate cross-functional teams on data collection, model training, and deployment.
- Manage timelines, milestones, and deliverables in line with project objectives.
Stakeholder Engagement and Knowledge Dissemination
- Collaborate with meteorological agencies, academic institutions, and industry partners.
- Present research findings at workshops, conferences, and policy forums.
- Publish results in peer-reviewed journals and present at leading conferences.
- Contribute to open-source codebases, datasets, and technical documentation.
Requirements
Essential Qualifications & Experience:
- PhD (or equivalent experience) in Meteorology, Climate Science, Machine Learning, or related field.
- Proven track record in AI or statistical modelling for climate or weather applications.
- Experience working with geospatial and gridded datasets (e.g., ERA5, CHIRPS, satellite data).
- Knowledge of numerical weather prediction (NWP) systems and data assimilation.
- Proficiency in Python.
- Excellent communication skills required, including the ability to convey complex ideas clearly to both technical and non-technical audiences.
- Strong publication record and ability to communicate research to diverse audiences.
Desirable Skills & Experience
- Experience working with African climate datasets and/or in data-sparse contexts.
- Experience with MLOps tools (e.g., MLflow, Kubeflow, Airflow, Docker, Kubernetes) for model lifecycle management.
- Proven experience in setting up project workflows and using tools such as Jira, with a strong understanding of agile methodologies, including Scrum.
- Experience in cloud-based ML workflows (AWS, GCP, Azure) and GPU/TPU environments.
- Expertise in bias correction, ensemble forecasting, and probabilistic skill assessment.
- Experience in engaging with policy and decision-making communities.
- Familiarity with open science and FAIR data principles.
- Company
- AfriClimate AI
- Employment Type
- Full-time
- Experience
- 2-5 years
- Location
- South Africa, Johannesburg (remote)