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, or as soon as possible after that. The Department of Electrical and Computer Engineering is organized into sections. The position is anchored in the "Signal Processing and Machine Learning" section [1
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-ence with machine learning, data analytics, big data handling and analysis, data engineering and management, and general competences in digitalization. You are familiar with Generative AI at theoretical
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applicant: has a PhD degree in electrical, computer or biomedical engineering, computer science, data mining/machine learning, or a closely related area. has demonstrated the ability to perform independent
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(more...) High Energy Physics / Machine Learning , Theoretical Particle Physics Fundamental Theory/Cosmology Appl Deadline: (posted 2025/01/20, updated 2025/01/19, listed until 2025/07/01) Position
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DTU Tenure Track Assistant Professor in Nutrient-Focused Processing in Ultra-Processed Food Syste...
, bioactive compounds, and other key nutrients. Develop and apply machine learning and modeling techniques to analyse, predict, and optimize the effects of processing on food composition, food Ingredient
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for Industrial Mechanics is located at SDU's beautiful campus in Sønderborg, in the inspiring building of Alsion, which is a center for science, culture and learning in the heart of Sønderborg and perched
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Machine and Deep Learning – Applications and Case Studies in Business Artificial Intelligence and Generative Artificial Intelligence in Business Explainable AI (XAI) Ecommerce, Web and Social Media
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Job Description If you have solid practical experience in embedded systems, computer engineering, or related areas — and are excited to teach, collaborate, and shape the next generation of engineers
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, bioactive compounds, and other key nutrients. Develop and apply machine learning and modeling techniques to analyse, predict, and optimize the effects of processing on food composition, food Ingredient
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. These include, but not limited to: Research Question 1: How can multimodal UAV data (RGB, thermal, LiDAR, hyperspectral) be fused using machine learning to predict complex canopy traits such as water-use