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Student (f/m/d) in Quantum Algorithms for Droplet and Bubble Oscillation Dynamics Modelling. Your tasks Development and implementation of numerical and algorithmic methods for the simulation of fluid
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learning, large language models, and the theory of deep learning. The candidate will develop DRL algorithms for online and off-line tasks, for robotic applications and possibly for LLM reasoning applications
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. This position is to be filled at the Institute of Climate and Energy Systems - Energy Systems Engineering (ICE-1), where we develop models and algorithms for the simulation and optimization of future energy
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unsupervised techniques, time-series modeling, and clustering algorithms. The candidate is expected to lead an effort to prepare generalized ML techniques for data quality monitoring for tasks across multiple
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Engineering, Neuroscience, or related fields. Tasks to be performed: Collection of experimental data in humans, development of neural decoding algorithms from bioelectrical signals, and development of a
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experimental settings. In addition to fieldwork, the PhD candidate will contribute to the development of novel inversion algorithms for EMI and GPR based on full-waveform inversion techniques. These methods aim
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focuses on modeling IoT-Fog environments, designing multi-objective optimization algorithms (latency, energy, reliability), and developing strategies for critical IoT applications like smart cities and
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postdoctoral research project. The project focuses on the development and application of a remote sensing algorithm for monitoring the physicochemical properties of aerosols based on optical measurements taken
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models were successfully developed with methods of Quantum Machine Learning. In cooperation with the University partners the aim of this project ls to translate classical analysis and simulation algorithms
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the mathematical models necessary for the development of the project. The following two months will be devoted to the study of the theoretical properties of these models. From the fifth month to the eighth month