A funded Data Science and Machine Learning Fellowship in Cape Town is offering recent MSc, PhD and first-class Honours graduates the opportunity to apply their quantitative skills to climate science, artificial intelligence and real-world climate solutions. The Climate Risk Lab is recruiting talented graduates with backgrounds in data science, machine learning, computer science, mathematics, statistics, econometrics, engineering, physics and related quantitative fields. The full-time, one-year fellowship will be based in Cape Town and is expected to begin in February 2027, with the possibility of a one-year renewal based on performance. There may also be potential for the fellowship to develop into a PhD scholarship or Postdoc funding. Applications are being accepted on a rolling basis until the position is filled, making early applications particularly important. About the Climate Risk Lab Fellowship The Climate Risk Lab’s mission is to create breakthrough science, tools and policies that help protect people and nature from climate change. Its research includes developing models to understand the past impacts of climate change and predict future impacts on people and nature. The Lab also works on using artificial intelligence to synthesise evidence about what works in climate solutions for human health and wellbeing. The Data Science and Machine Learning Fellowship is designed to strengthen the Lab’s capacity to deliver this research while helping successful candidates develop their own research and data science skills. Fellows will provide data science support to an interdisciplinary team working with climate, environmental, health and socioeconomic data. At the same time, fellows will be encouraged to lead a project that is meaningful to them. Who Can Apply? The fellowship is particularly suited to recent graduates who have strong quantitative and programming skills and are interested in applying them to climate-related challenges. Applicants must meet the minimum academic and technical requirements, including: An MSc or first-class Honours degree, either completed or in the final year, in data science, machine learning, computer science, mathematics, statistics or a related field. Proficiency in programming languages, preferably Python or R. A solid grounding in statistics and/or data science principles. Excellent written and oral communication skills. The call also welcomes applications from candidates with a PhD background whose expertise aligns with the fellowship. The Climate Risk Lab particularly encourages applications from historically underrepresented groups in these fields, including female-identifying people of colour. What Will Fellows Do? Successful candidates will contribute to a range of data-intensive research activities within the Lab. Responsibilities may include analysing large climate, environmental, health and socioeconomic datasets; developing and applying AI tools to improve data science workflows; and supporting other analysts in using AI technologies. Fellows will also be expected to download, clean, process and optimise large datasets while helping establish reproducible research practices. Other responsibilities include contributing to and maintaining Git repositories, documenting and communicating workflows, and developing code that improves the processing and analysis of large spatial-temporal datasets. The role may also involve using parallel computing approaches to improve computational efficiency. Importantly, fellows will have the opportunity to lead or co-lead a research project that could contribute to a peer-reviewed publication, toolkit or dataset. International travel may also be required when necessary. Mentorship and Research Opportunities The fellowship offers more than technical work. Each fellow will be paired with a senior data scientist or postdoctoral researcher who will provide mentorship throughout the position. Fellows will also have opportunities to lead data-intensive research within the Lab and participate in working group meetings involving international collaborators and/or conferences. This could provide valuable exposure to interdisciplinary climate research and international scientific collaboration. Desirable Skills While the minimum criteria are important, applicants with additional technical experience may be particularly competitive. The Lab lists experience with R and Python packages such as xarray, pandas, NumPy, Zarr, netCDF4, terra, tidyverse, Arrow and DuckDB among its desirable skills. Experience with Bash, Linux and high-performance computing environments, agentic AI tools, GitHub and large spatial-temporal datasets is also considered an advantage. Candidates do not necessarily need every desirable skill to apply, provided they meet the minimum requirements and can demonstrate strong quantitative and programming abilities. Documents Required Applicants must submit their materials as a single PDF file. The application should include: CV, including a statement indicating whether the applicant holds a valid South African work or study permit. Names, positions and email addresses of two professional referees, included in the CV. Cover letter explaining why the applicant is a good fit for the fellowship. Academic transcript. Links to GitHub repositories, Jupyter notebooks or other examples of written code, if available. Personal website and/or LinkedIn profile, if available. Applicants should ensure that their application clearly demonstrates their quantitative, programming, research and communication capabilities. Application Deadline Applications are being accepted on a rolling basis until the position is filled. The Climate Risk Lab has indicated a preference for the successful applicant to begin in February 2027. The first reviews of candidates will begin in October 2026, and shortlisted candidates will be invited to a technical interview. Because applications are reviewed on a rolling basis, interested graduates are encouraged to apply early rather than waiting for the position to close. Application Form: https://forms.gle/bjVBrhMJzQDAjPNN7 Remuneration The fellowship offers remuneration that will be competitive with academic and market rates, with the final level based on the candidate’s experience. The fellowship is full-time for one year, with an opportunity for a one-year renewal depending on performance. There may also be potential for the fellowship to develop into PhD scholarship or Postdoc funding, creating an additional pathway for candidates interested in continuing their research careers. Who Should Consider Applying? This opportunity could be particularly relevant to graduates who want to combine data science, machine learning and quantitative research with climate action. Candidates interested in climate modelling, environmental data, artificial intelligence, health impacts, socioeconomic analysis, reproducible research or large-scale spatial-temporal datasets may find the fellowship especially relevant. It could also be a strong opportunity for graduates looking to gain professional research experience while working alongside senior researchers and international collaborators. Questions about the fellowship: Puja Pande — puja.pande@uct.ac.za FIND FULL CALL HERE For more opportunities such as these please follow us on Facebook, Instagram, Twitter, LinkedIn and WPChannel Disclaimer: Global South Opportunities (GSO) does not take ownership or credit for the opportunities shared on this platform. All opportunities are sourced from official announcements and external sources for informational purposes only. Applicants are encouraged to verify all details, deadlines, and eligibility requirements from the official source before applying. Opportunities may be updated or changed by the providing organisations.