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environment. Develop robot localization approach leveraging data from multiple sensors including but not limited to camera and lidars. Develop efficient approach for multi-robot trajectory planning and tracking
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research that covers the energy value chain from generation to innovative end-use solutions, motivated by industrialisation and deployment. ERI@N has multiple Interdisciplinary Research Programmes which
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, attending local and/or international conferences Mentor and supervision of undergraduate/ PhD students and junior research staff Key Competencies and Education Requirements: PhD in Biological Sciences, Food
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community. Required Skills and Qualifications: Minimum PhD in computer science/ engineering or related fields. Proficiency in Python is a must. Experience with other programming languages such as Java, C/C
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diseases and ageing, and have multiple national and international collaborations. Key Responsibilities: Perform tasks and support all aspects of the research project. Conduct accurate monitoring, documenting
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diseases and ageing, and have multiple national and international collaborations. Key Responsibilities: Perform tasks and support all aspects of the research project. Conduct accurate monitoring, documenting
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diversity, foster a democratic and constructivist view of knowledge and knowledge construction, and promote an equitable and just learning environment. Requirements: - PhD or EdD in Educational Policy
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to the work described herein, including contributing to occasional admin and coordination activities. Qualifications PhD in infectious diseases or other related disciplines, with a strong focus on pathogen
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: A PhD in Physics, Computer Science, Mathematics, Machine Learning or relevant fields. Strong publication record in top conferences/journals, such as Nature Physics, Nature Communications, PRL, T-PAMI
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decision-making and research findings. Qualifications & Competencies: Minimally a PhD degree in Artificial Intelligence, Computer Science, Optimization, or a related field. Strong foundation in multi-agent