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are now looking for a Doctoral candidate (m/f/d) on the development of optical clocks Your tasks Enrollment at a partner university (Humboldt-University Berlin, Group for Integrated Quantum Sensors) as a
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energy use more efficient. We develop new optimization methods, machine learning algorithms, and prototypical energy management systems (EMS) controlling complex energy systems like buildings, electricity
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computing, domain-specific multi- and manycore architectures, networks-on-chip (NoCs), methods and algorithms for application parallelization, simulators and virtual platforms for application- and
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scalable database of sensor and process data is being created, which serves as the basis for ML models for component segmentation, strategic path planning and process optimisation. The aim is to enable data
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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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detectors (Partial) automation of detector characterization for more efficient analysis Algorithm development: Development of a correction method based on information field theory for atmospheric image
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the areas of ‘Process Sensors and Systems Engineering’, ‘Material Analytics’ and ‘Computational Methods’. With our expertise in data science, modelling and systems engineering, we develop tailor-made
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multi-parameter ion-beam tuning procedures (collaboration with Univ. of Vienna and HZDR) and developments of machine learning (ML)-algorithms for optimization of beam parameters and control of relevant
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that process planning has a high potential for automated optimization. Building upon this, you will advance our optimization pipeline and evaluate different optimization algorithms/strategies. What you will do
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of the novel methods created within our research group. Your primary tasks will include: - Assisting in the research taking place in our group. - Collaborating with our researchers to translate new algorithms