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                Engineering, or a foreign degree deemed equivalent, in Electrical Engineering or related fields, or equivalent competence considered relevant by the employer. Strong knowledge in control and optimization theory 
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                such as Matlab, or Python. Excellent command of spoken and written English. Additional qualifications Experience with modelling, simulation, and optimization of energy systems. Experience in thermodynamic 
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                . Excellent command of spoken and written English. Additional qualifications Experience with modelling, simulation, and optimization of energy systems. Experience in thermodynamic analysis, particularly 
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                the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates expertise from machine learning, optimization, control theory, and applied mathematics 
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                decision-support tools for energy-aware planning, predictive maintenance, and resource optimization, -use robotics, autonomous systems, IEC 61499, and digital twins to design and evaluate distributed control 
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                . Our research integrates expertise from machine learning, optimization, control theory, and network science, spanning diverse application domains such as energy systems, biomedical systems, material 
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                vaccines that display the selected epitopes in a controlled and optimized manner. Qualifications Requirements for the Position: A Master of Science in Biotechnology, Biomedicine, or Molecular Biology 
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                . Our research integrates expertise from machine learning, optimization, control theory, and network science, spanning diverse application domains such as energy systems, biomedical systems, material 
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                essential tool for training and testing of AI models and control systems for robots and autonomous vehicles. In a digital environment, large amounts of annotated training data can be created safely and easily 
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                essential tool for training and testing of AI models and control systems for robots and autonomous vehicles. In a digital environment, large amounts of annotated training data can be created safely and easily