IBM Research Scientists are charting the future of Artificial Intelligence, creating breakthroughs in quantum computing, advancing climate and sustainability science, and much more. Join a team that is dedicated to applying science to some of today's most complex challenges, whether it's developing AI-powered warning systems for vulnerable communities, leveraging quantum computers for drug discovery, or building foundation models to revolutionize the domains of language, geospatial, healthcare, and much more.
IBM is excited to announce the opening of a Student Internship at the South Africa Research Lab in Johannesburg, South Africa. This is a unique opportunity to work on groundbreaking Foundation Model Technologies, develop cloud-based scalable software systems, and to collaborate with hundreds of leading research scientists and engineers across the globe from the world's largest industrial research labs. IBM Research Africa is looking for an M.Sc- or Ph.D-level intern to join their team to work on an exciting project in the field of urban climate, leveraging geospatial foundational models developed by IBM Research. Foundational models are flexible, re-useable models that can be applied to many downstream tasks. These models are replacing task-specific models that have been in place for the past decade. For this role, you will be expected to develop processing pipelines for geospatial data, fine tune IBM's geospatial foundation models using the TerraTorch package, and validate model outputs with observations.
* Currently enrolled in an M.Sc. or Ph.D program from an accredited university in a quantitative field such as Computer Science, Machine Learning, Data Science, Statistics, Computer & Electronics Engineering, or Physics
* Proficiency in coding with the scientific Python stack (numpy, scipy, pandas, matplotlib, etc.) and experience in at least one additional programming language such as Java, JavaScript, NodeJS, C/C++, etc.
* Experience working with machine learning and deep learning programming packages such as PyTorch and TensorFlow.
* Ideally, have experience working with geospatial and spatiotemporal data, transformations, and file formats (netCDF, GeoTiff)
* Strong problem-solving and analytical skills, as well as good communication and collaboration skills.
* Experience presenting research in technical communities (e.g., Neurips, CVPR, ICML, ICLR, IJCAI, AAAI, KDD, IEEE QCE).
* Experience with cloud-native technologies and platforms.
* Deep understanding of machine learning concepts, foundation models, and some experience in MLOps.
* Familiarity with developing and using APIs.