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Field
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Design). Ideal candidates have Specialist Knowledge in Neuromorphic Engineering, with experience in Designing and Building and Implementing FPGA systems, working with and/or developing neuromorphic
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-inspired selection). 3-Investigate the integration of QIEC with Quality-Diversity (QD) algorithms such as MAP-Elites.(month 2-3) 4-Explore the use of Evolutionary Computation to generate and optimize quantum
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software architecture. Drive research and development of algorithms for natural language understanding, structured command generation, and domain-specific model adaptation or fine-tuning. Integrate NLP and
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allows us to better plan our cities, and new approaches have been made possible with the widespread use of smartphones carrying several different sensors. As a matter of fact, in most developed countries
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from a variety of national and international funding agencies, as well as from industry. Job description We are seeking an ambitious candidate to develop Machine Learning models and frameworks for time
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-funded AI research group “Fusing Deep Learning and Statistics towards Understanding Structured Biomedical Data (DeSBi)” development of deep neural networks and machine learning algorithms for the analysis
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National Lab, University of Tokyo etc.), the PhD candidate is expected to research on some of the following themes: New algorithms for parallel/distributed AI/ML Hardware-aware and resource-efficient
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 10 days ago
information about staff equity at ANU, visit https://services.anu.edu.au/human-resources/respect-inclusion We welcome and develop diversity of backgrounds, experiences and ideas and encourage applications from
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advantageous. Proficiency in algorithm development using Python will be advantageous Where to apply Website https://www.timeshighereducation.com/unijobs/listing/403869/research-fellow-ai-… Requirements
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of precipitation and temperature over Morocco. Key Responsibilities: Statistical model development: Led the development of advanced statistical models and machine learning algorithms for forecasting precipitation