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into the digital world. An evaluation based on the combined information from various sensors is to be carried out for optimal monitoring of the processes. What you will do You will be responsible for expanding
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and evaluation of innovative data- and machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods
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if they are equally suitable. Our tasks are varied and customisable - we work together with applicants with disabilities to find solutions that optimally promote their abilities. The same applies if they do not fulfil
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Your Job: As part of the on-going EU project – LOCALISED (https://www.localised-project.eu/), this thesis focuses on integrating regional climate adaptation measures into an existing optimization
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benefits, such as diagnosing joint injuries. We mainly use simulations, mathematical motion and shape models, and optimization methods. For building simulations, we use classical image processing and deep
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in solar energy by exploring fundamentally the controversy regarding the abnormal evaporation rate and simulate/ predict vapor production rate to guide the design of an optimized interfacial evaporator
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Sciences and Systems in the lab of Professor M. Bichler. We offer: - a team of young and highly motivated colleagues who are passionate about machine learning, optimization, and game theory. - strong support
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revolution is increasing the flexibility of industrial production and optimizing it by linking traditional production with new technologies such as IoT sensors, edge and cloud systems. This heterogeneous
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qualified. Our tasks are varied and customisable - we work together with applicants with disabilities to find solutions that optimally promote their abilities. The same applies if they do not fulfil all
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a varied range of tasks. A collegial, pleasant and motivating working environment. Flexible working hours and thus the optimal compatibility of studies and practice. We value and promote the diversity