Research Scientist Internship Johannesburg, ZA
Cloud
Intern
Introduction At IBM Research we’re a group of researchers, scientists, technologists, engineers, designers, and thinkers inventing what’s next in computing. We’re spread across the globe, with 17 labs located on five continents. At IBM Research Africa, work is more than a job – it’s a calling: To build. To design. To code. To invent. To collaborate. To think along with partners about some of the continent’s and the world’s greatest challenges. Not just to do something better, but to attempt things differently to how they are approached elsewhere in the world. Your Role and Responsibilities We are seeking a Research Scientist Intern currently enrolled in a STEM Master’s degree at a South African University. Ideal candidates would have a background in computer science, machine learning, natural language processing and/or familiarity with geospatial, remote sensing, or biomedical data. Good communication skills and the ability to work independently and as part of a team are highly desired traits. We are seeking a team player who is motivated by addressing complex data analysis problems, including learning from less and heterogeneous spatial and temporal data. We want someone who is interested in interdisciplinary & transdisciplinary collaboration with the scholarly community, business units within IBM, and with external partners and clients. In this unique role, you will interact with the brightest minds in AI and will help bring AI research ideas into scalable, robust systems. Your can-do approach to creative problem solving will be critical to the success of our teams and the company. You must be willing to work in Johannesburg, South Africa. Required Technical and Professional Expertise
Pursuing an M.Sc in machine learning, artificial intelligence, computer science, applied mathematics, signal processing, statistics, or related technical fields with extensive depth in advanced mathematics, statistics, and programming
Proficiency in programming languages such as Python, R, or C/C++
Familiarity with tools such as Git/GitHub
Theoretical knowledge of and hands-on proficiency in machine learning/deep learning algorithms
Familiarity with natural language processing, geospatial and temporal data processing, biomedical data analysis, or quantum computing
Familiarity with one or more machine/deep learning frameworks, such as Scikit-Learn, PyTorch, or TensorFlow
Experience with parallel computing, DevOps, or containerization will be advantageous
Good communication skills in English will be required
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