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Field
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Predictive and optimization-based control of smart grids: theory and algorithms School of Electrical and Electronic Engineering PhD Research Project Self Funded Dr P Trodden Application Deadline
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flow are significantly increased across various new entities such as distributed energy sources. This will lead to additional information and communications requirements, as well as new information
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distributed tasks such as inspection of a big geographic area for fires is an important objective of this project. The project aims are to: 1) provide methodological contributions towards intelligent sensing
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related to the position: AOCS subsystem architecture, design, testing and verification (including control design algorithms, analysis and simulation) Pointing error engineering Smallsat and nanosat AOCS
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group of experts to predict (probabilistically) whether these occupations will be automated, augmented or unaffected by emerging technologies. Using this data, a classification algorithm is then trained
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Astronomical Institute, the last 2 years at Tartu Observatory. The PhD research project has the purpose to analyze and combine the weblike distribution of galaxies in large galaxy redshift surveys, with
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: Algorithm Design and Analysis CSE 107: Introduction to Digital Image Processing CSE 108: Full Stack Web Development CSE 111: Database Systems CSE 120: Software Engineering CSE 160: Computer Networks CSE 168
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Structures CSE 031: Computer Organization and Assembly Language CSE 100: Algorithm Design and Analysis CSE 107: Introduction to Digital Image Processing CSE 108: Full Stack Web Development CSE 111: Database
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: Algorithm Design and Analysis CSE 107: Introduction to Digital Image Processing CSE 108: Full Stack Web Development CSE 111: Database Systems CSE 120: Software Engineering CSE 160: Computer Networks CSE 168
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, machine learning algorithms, and prototypical energy management systems (EMS) controlling complex energy systems like buildings, electricity distribution grids and thermal energy systems for a sustainable