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focuses on the development of secure and trustworthy AI for resource-constrained embedded systems. The research will investigate how machine learning models can be designed and deployed efficiently
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should have the following qualifications: Ph. D. degree in data science, electrical engineering, computer engineering, computer science, mathematical engineering, or similar. Proven track record in
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analysis, causal inference with machine learning, and deep learning for various health-related domains. The Global Pathogen Analysis Platform (GPAP) is a new international initiative to strengthen global
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Machine and Deep Learning – Applications and Case Studies in Business AI Agents and Agentic Workflows in Business Explainable AI (XAI) E-commerce, Web and Social Media Analytics Big data analytics Natural
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implement a hyperspectral imaging system tailored to bulk forensic trace analysis and develop chemometric and machine-learning models for material identification and classification. You will evaluate
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electrical engineering, control engineering, applied mathematics, computer science, or a related field A strong background in probability and statistics, machine learning, or control theory Interest in cyber
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. Qualifications Applicants at Postdoctoral Researcher level should hold a PhD in AI enabled learning, educational technology, information systems, computer supported learning, social entrepreneurship, innovation
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Design. In addition, the project involves close collaboration with the Department of Architecture, Design, and Media Technology and involves one other PhD candidate and a postdoctoral researcher. The
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at Aalborg University's Technical Faculty for IT and Design. In addition, the project involves close collaboration with the Department of Architecture, Design, and Media Technology and involves one other PhD
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of bioacoustic signals. Extensive experience with programming (Matlab, R, Python) including GPU programming is required, and familiarity with edge-based machine learning (particularly sound event detection), open