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where appropriate. About You PhD in the broad area of Computer Science/Engineering and/or Applied Mathematics Detailed and highly specialised knowledge and understanding of Computer Vision, Deep Learning
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and apply Deep Learning tools for protein modeling, small molecule docking, and structure prediction. • Collaborate with interdisciplinary teams to advance research goals and contribute to scientific
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PhD student within Machine Learning in IoT edge devices, your primary mission is to drive advancements in the areas of Machine Learning, Deep Learning and efficient implementations in IoT devices and
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surface vessels. Using state-of-the-art deep learning models together with various environment sensing methods, the candidate is required to devise novel solutions that can help interpret the environment
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friendly refrigeration [1]. To do so, this PhD aims to develop original modeling methods, based on the development of Machine Learning tools, allowing for the description of complex molecular systems
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sequences, and to develop new methodology to predict conformational diversity and changes using machine learning. With the help of deep-learning approaches methods to predict flexibility, conformational
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) to study how new (virtual) technologies may contribute to creating learning opportunities for tourists regarding human-created climate change. There will be a strong focus on developing deep working research
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reaction mechanisms remain not fully understood. To address these gaps, we are utilizing AI to autonomously identify chemical reaction mechanisms. Our approach combines deep learning for predicting potential
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(s) extension on related projects. As part of your roles, you will design and develop ML algorithms that make deep learning models learn on the fly and solve multiple tasks efficiently on embedded
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. Mingjie Liu, focusing on the development and implementation in advanced machine learning and deep learning models to predict new materials and molecule properties. This one-year appointment is renewable