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detection of respiratory viruses and optimize pandemic response strategies? Then we are looking for you! Join our FWO-SBO project ANTICIPATE, a collaboration between the University of Antwerp, VUB and the
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resource-constrained environments, and it is important to investigate whether features derived from different network layers can be effectively combined. Machine Learning Model Development & Optimization
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Your Job: You will join the "Electrocatalytic Interface Engineering" department, led by Prof. Dr.-Ing. Simon Thiele, and the "Membrane Polymer Synthesis" (MPS) team by Dr. Jochen Kerres
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/ Robust) Combinatorial Optimization, Game Theory, and Network Theory, as well as Artificial Intelligence. Potentially, scenarios could be simulated using agent-based, discrete-event, or other techniques
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on building the next generation of quantum processors based on superconducting circuits. To achieve this ambitiuous goal, we have a variety of projects related to: Development and optimization of nano
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the renewable energy colleagues at IMT Elucidation of the dominant separation mechanisms, to achieve both fundamental understanding and optimized process performance The PhD project will be predominantly
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optimal operating conditions and followed by surface analysis techniques (e.g. Scanning electron microscope, X-ray diffraction for residual stress measurements, Electron Back-Scattered Diffraction and
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/f/d, E13 TV-L, 50-75%) The position is limited for three years. Description of the project The research group of Prof. Dr. Frank Schreiber at the University of Tübingen deals with the physics
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inorganic AEMWEs by integrating the perovskite electrolyte with perovskite electrodes from cell fabrication to cell configuration optimization and to single cell performance. Significance The project has
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to: - Developing underwater communication systems using deep learning which are well-performing to nonlinear channels. - Establishing a deep learning architecture which is optimal for underwater acoustic