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environment such as Matlab/Simulink. Design and develop an intelligent energy management system for the e-vessel microgrid for coordinated control of multiple energy sources considering cost, carbon, and
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research subject for this position is development of distributed processing strategies and algorithms for Large Intelligent Surfaces, including both joint baseband processing and synchronization across
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of HLA donor search algorithms and other non-HLA factors, such as ABO, age and CMV status. Analyze donor searches and apply current donor selection algorithms and strategies. Responsible
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of AI for the integration of multimodal healthcare data specifically incorporating patient preferences. This includes investigating new methods but also designing and benchmarking integration algorithms
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. Numerical Analysis and Scientific Computing, developing numerical methods and algorithms that are accurate, efficient, and robust with respect to challenges that manifest in the simulation of complex
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designing and benchmarking integration algorithms. The position is situated in the Intelligent Data Engineering Lab and will be supervised by Dr. Jan-Christoph Kalo and Prof. Paul Groth. What you will do
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, integrating five innovations. First, you will establish material accountancy algorithms using Monte Carlo simulation and Bayesian inference to distinguish normal tritium losses from suspicious discrepancies
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that reduce raw data at the sensor level. You will develop AI and machine learning algorithms for anomaly detection, pattern recognition, and efficient data compression. To ensure practical usability
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sampling-based and reinforcement learning-based motion planning algorithms for multiple robotic arms in automotive manufacturing, including testing, performance evaluation in both simulation and actual
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from multiple systems and sources to answer key operational questions. Deep experience using a variety of data mining/data analysis methods to build and implement dashboards, models and algorithms