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Field
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). Information Key Responsibilities: Develop a generalizable and explainable (gray-box) model for adaptive patient monitoring. Utilize a mixed approach combining real and synthetic data for algorithm development
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Application deadline: 15 March 2026 Apply now This position focuses on fundamental open problems in algorithm design and computational complexity. The main theme will be a unifying theory of algorithmic power
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numerical modeling and validation of brain-inspired algorithms Develop circuit-plausible training and inference algorithms, and analyze their behavior in LTspice and Cadence Spectre Perform algorithm–circuit
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microscopy is often limited by slow acquisition speeds and large volumes of redundant data, restricting its applicability in real-world scenarios. The goal of this PhD project is to develop a snapshot spatio
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(Berlin) in a close partnership with the Forschungszentrum Jülich, contributing to algorithm development, computational tool implementation, and validation with experimental partners (TU Graz and
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The Fraunhofer Institute for Algorithms and Scientific Computing SCAI in Sankt Augustin, near Bonn, has around 180 employees who research and develop innovative methods in the field of computational
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Technology Centre (MTC). You will push the limits of multiphysics CFD for laser manufacturing by developing a next-generation simulation capability for laser drilling - with relevance to additive
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through theory and simulation and/or experimental design and testing; developing new image reconstruction algorithms for providing more information with less radiation; and applying our techniques
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this issue and we could use obtain data-driven models using machine learning algorithms such as artificial neural networks, reinforcement learning, and deep learning. A typical caveat of data-driven modelling
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candidate will develop and conduct empirical research examining human interaction with algorithmic decision-support systems in clinical contexts. The precise focus of the project will be refined