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Field
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with major in Power Engineering • Relevant experience in power electronics, drives, control algorithms, optimization techniques, and optimal energy management algorithm development for the optimal
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-holomorphic Hilbert Modular Forms”. The central aim of the project is to develop explicit algorithms for computing with non-holomorphic Hilbert Modular Forms and using these algorithms together with theoretical
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. Integrate and automate manufacturing equipment (e.g., CNC machines, industrial robots, PLCs, machine vision systems) within a smart factory environment. Develop data acquisition pipelines using sensors, IIoT
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technologies, ethical implications, and governance frameworks, including knowledge of algorithmic accountability and transparency. Experience with both qualitative and quantitative research methods, and
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power engineering. In condition monitoring non-invasive data is analyzed through machine learning algorithms or by statistical methods. The aim of predictive analysis is to use non-invasive methods
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and dynamic models. Development of optimization algorithms for the unique operational characteristics of the onshore microgrids. Development energy management system including frontend and backend. Job
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operation of the umFm module unit used in vertical farm which includes handling of soil compost, irrigating of the crops and taking note of the sensors incorporation in the vertical farm inhouse. Job
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digital techniques for advanced process control, including but not limited to: AI-enabled smart sensors Digital twinning Remote Operations and Security Novel communications technologies for mobile assets
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part of the ‘REMIX -TUNE - Redefining The Role Of Mixing In Ocean Overturning And Ventilation’ ERC Consolidator project, which seeks to leverage emerging sensor capabilities of autonomous profiling
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Experience: Knowledge of AI frameworks and algorithms, particularly those related to decision-making and ethical AI. Machine Learning Experience: Knowledge of ML techniques, including reinforcement learning