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language processing (NLP), large language models (LLMs), machine learning (ML), and data visualization. The candidate will leverage their expertise in AI, statistics, and programming to design, develop, and evaluate
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partner organizations in Kenya. Qualifications: Expertise in a relevant discipline (e.g., epidemiology, ecology, nutrition, economics) with PhD conferred by the start of the position Demonstrated expertise
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alongside longstanding regional partner organizations in Kenya. Qualifications: Expertise in a relevant discipline (e.g., epidemiology, ecology, nutrition, economics) with PhD conferred by the start of
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integrating local flexibility markets through distributed AI-based coordination, market mechanism design, and cloud-to-edge computing. It aims to develop scalable machine learning methods for coordinating grid
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field. Experience: At least three years of strong record of research productivity in machine learning and artificial intelligence. Expertise in AI/ML and interests in business and policy applications
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methods of detection, identification, classification and tracking of objects of different sizes, shapes and speeds of movement using elements of artificial intelligence and machine learning. • Research work
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Overview Nature offers a mechanism - called homeostasis - by which life forms can maintain their physical integrity and well being. On the other hand, a series of machines, including robots, cannot
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validating deep learning models for the prediction of disease progression from ophthalmic data. Skills include working with image or computer vision-based toolkits, development of multimodal, multidata type
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positions (TV-L E13). Addressing global challenges, the school provides a wide variety of topics, from logic in autonomous cyber-physical systems to machine learning in Earth System models. You will have one
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of progressive methods of detection, identification, classification and tracking of objects of different sizes, shapes and speeds of movement using elements of artificial intelligence and machine learning