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Field
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Responsibilities Development of new machine learning modeling approaches Development of new advanced control and optimization algorithms Optimization of carbon capture process operation Provide regular project
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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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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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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
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electronic systems with a focus on inverters and active filter-based harmonic mitigation, thermal performance, and control strategies. Develop and implement advanced control algorithms for real-time operation
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formats. Experience with AI and deep learning algorithm development for medical image analysis. Familiarity with SQL, Python, Tensorflow, Scikit-Learn, and Pandas. Additional Qualifications Considered
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control strategies. Develop and implement advanced control algorithms for real-time operation and performance enhancement of power electronic converters and transformer-based solutions. Perform hardware-in