In a world where every plate quietly shapes one’s health, the question is no longer just what we eat, but what lies within it. Yet for millions managing medical conditions or striving for healthier lifestyles, decoding the right amount of nutrients in everyday foods has long been a challenge, often relying on guesswork, labels, or expert knowledge that most people simply don’t have at their fingertips.
KENET is mandated, among other things, to facilitate research collaboration among member institutions. This is done through three Special Interest Groups (SIGs), namely, Computer Science and Information Systems (CSIS), Computational Modelling and Materials Science (CMMS), and Engineering. Each SIG is coordinated by a part-time Research Associate, who is usually a senior faculty member or researcher in the respective academic area.
Artificial Intelligence continues to have great impact on the education sector and is forcing academics to adapt how they teach and assess learning outcomes. In Kenya, the impact of AI is compounded by the limited resources available at most of our institutions of higher learning. In addition, to effectively take advantage of the AI opportunity, STEM education must be enhanced to keep up with emerging trends and to prepare graduates capable of leveraging AI and other technologies for problem solving.
Artificial Intelligence continues to have great impact on the education sector and is forcing academics to adapt how they teach and assess learning outcomes. In Kenya, the impact of AI is compounded by the limited resources available at most of our institutions of higher learning. In addition, to effectively take advantage of the AI opportunity, STEM education must be enhanced to keep up with emerging trends and to prepare graduates capable of leveraging AI and other technologies for problem solving.
This call for proposals seeks to support early-career researchers in advancing emerging areas of Artificial Intelligence through work that combines technical depth with demonstrable, real-world implementation. The grant is designed to catalyze the development of innovative ideas into functional pilots or prototypes that can be tested, refined, and shared as practical reference models.
This call seeks to fund engineering research in Kenyan universities or research institutions that leverage advances in AI and exploit both the computational and LoRaWAN infrastructure installed by KENET. In addition, this call seeks to support early-career PhD faculty and/or researchers in advancing emerging areas of Artificial Intelligence through work that combines technical depth with demonstrable, real-world implementation.
The Computational Modeling and Materials Science is a Special Interest Group supported by KENET to enhance research capacity development in the use of computational modeling in science and technology. Research work is expected to involve university faculty and graduate students in Chemistry, Physics and Environmental Sciences but strongly welcomes those from other basic and applied sciences.
This call for proposals seeks to support early-career researchers in advancing emerging areas of Artificial Intelligence through work that combines technical depth with demonstrable, real-world implementation. The grant is designed to catalyze the development of innovative ideas into functional pilots or prototypes that can be tested, refined, and shared as practical reference models.
This call seeks to fund engineering research in Kenyan universities or research institutions that leverage advances in AI and exploit both the computational and LoRaWAN infrastructure installed by KENET. In addition, this call seeks to support early-career PhD faculty and/or researchers in advancing emerging areas of Artificial Intelligence through work that combines technical depth with demonstrable, real-world implementation. The grant is designed to catalyze the development of innovative ideas into functional pilots or prototypes that can be tested, refined, and shared as practical reference models.
The Computational Modeling and Materials Science is a Special Interest Group supported by KENET to enhance research capacity development in the use of computational modeling in science and technology. Research work is expected to involve university faculty and graduate students in Chemistry, Physics and Environmental Sciences but strongly welcomes those from other basic and applied sciences.
