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-from-motion, and object recognition. The main research problems include mathematical theory, algorithms, and machine learning (deep learning) for inverse problems in artificial intelligence, as
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; they make sense to humans and are accessible to algorithmic techniques while neural models are adaptive and learnable. The aim of this project is to develop models which combine these advantages. The project
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the Department of Biology includes many of these specializations, from molecular biology to applied ecology, from viruses and individual cells to evolutionary biology and global biodiversity. Taking on research
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district heating networks, within the framework of the project "Data Analysis for Peak Load Stabilisation in District Heating Networks (DAS)". The work includes: design and implementation of RL algorithms
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Networks (DAS)". The work includes: design and implementation of RL algorithms to address the challenges of peak load variations in district heating systems development and use of simulation models
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, signal processing and/or wireless communication. Basic knowledge of and/or experience in working with reinforcement learning/other machine learning algorithms Excellent command of spoken and written
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to have good knowledge of computer science, mathematics, algorithms, and programming. Knowledge and experience in artificial intelligence and machine learning is expected, but not required. Knowledge and
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are broad, ranging from evolutionary ecology and genetics to studies of entire ecosystems. For more detailed information on our research, please see www.ieg.uu.se. ; The position will be affiliated with
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sciences . Project description The Johannesson lab at DEEP makes use of the unique lifestyles of fungi to explore evolutionary questions about individuality and genetic inheritance. The group is now looking
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. You have a strong ability to solve problems and formulate algorithms. You also have an interest in genetics and genomics. You are organized, proactive, and can work independently as