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that you will help us to build the sustainable companies and societies of the future. The Machine Learning Group at Luleå University of Technology seeks a doctoral student in machine learning. We offer well
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Engineering . You will be supervised by senior researchers with expertise in robotics, machine learning, automatic control, and optimization. The group leads and participates in numerous collaborative research
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series data. Large data sets come with significant computational challenges. Tremendous algorithmic progress has been made in machine learning and related areas, but application to dynamic systems is
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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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propagation, electromagnetics, optimization, machine learning, and networking. Strong documented experience in these areas is commendable, particularly by having published your work. Candidates should have an
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, undergraduate and postgraduate education in communications engineering, statistical signal processing, network science, and decentralized machine learning. Welcome to read more about us at: https://liu.se/en
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, electromagnetics, optimization, machine learning, and networking. Strong documented experience in these areas is commendable, particularly by having published your work. Candidates should have an excellent mastering
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. Its vast scope also benefits our undergraduate and graduate programmes, and we now teach courses in several engineering programmes at bachelor’s and master’s levels, as well as the programmes in
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a Research Infrastructure? No Offer Description Luleå University of Technology is in strong growth with world-leading competence in several research areas. We shape the future through innovative
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: Analyze spectroscopic and kinetic data, employ statistical and machine learning approaches where relevant, and contribute to manuscripts, presentations, and reports. Collaboration: Work closely with project