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immersive and interactive environments. • Definition and modeling of low- and high-level quality-related features. • Development and validation of objective quality assessment metrics for synthesized content
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basic principles of reinforcement learning and popular modern reinforcement learning algorithms. Students will develop familiarity with both model-based and model-free reinforcement learning algorithms
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The postdoctoral researcher will develop an approach
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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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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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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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-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 HEP experiments
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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