There is currently a great need in East Africa to build capacity for educational excellence in science, engineering and technology, which can help play a vital role in the economic and social transformation of East and Sub-Saharan Africa. The ultimate goal of the project is to promote capacity building by creating a broad network of knowledgeable scientists and researchers who will start to collaborate to tackle some of the most urgent problems in food security, environment, education, water and global health affecting Tanzania and neighboring countries. To this end, a three-week course will be organized to train 30 members of the mathematical, biological and engineering community in Tanzania, especially early career researchers, graduate and post-graduate students on multidisciplinary applications of mathematics. The proposed work will help create much-needed awareness to pursue multidisciplinary real-world problem solving using science, engineering, and technology, and, in turn, help increase the number of people involved in science, technology, engineering, and mathematics (STEM) in the country. This program is expected to be well received by the mathematics, biology and engineering communities in East Africa, where there is a great need to expose the next generation workforce of young talent to such multidisciplinary learning opportunities.
The proposed project will be modeled after and build upon a successful National Science Foundation Research Experiences for Undergraduates program that the U.S. partner currently directs. In particular, the selected participants will have the opportunity to learn about new content, software, and tools and apply them to solve real-world problems. Some of these proposed projects that the participants will learn about and work on include fish harvesting and its economic impact, social process modeling and bioconservation, optimization models for energy security, enhancing student learning in STEM, sensor networks to detect petroleum adulteration, mutualism models for rhizobia legume interaction, and prediction of tobacco concentrations using contaminant transport models coupled with disease dynamics.
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