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on the solid application of scientific research method. The department has a pluralistic approach to research methods that includes, for example, formal theoretical models, quantitative empirical methods such as
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. The project focuses on the intersection of deep reinforcement learning, probabilistic modeling, and bio-inspired architectures (such as Spiking Neural Networks) to achieve sample- and energy-efficient robust
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technologies Development and utilization of high throughput methods for characterizing and quantifying the physicochemical behavior of food macromolecules in complex matrices. Modelling and the use of machine
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activities may include first-principles simulations, electronic-structure theory, computational electrochemistry, multiscale and phase-field modelling, data-driven and AI-assisted materials modelling, and
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of these experiments. As part of this, we have developed new algorithms and a completely new web-based platform – EasyNMR - for performing such modelling/simulations. With this position, we seek to strengthen
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We are offering a PhD fellowship in “Agentic AI and Foundation Models for Global Pathogen Analysis” commencing September 1st, 2026, or as soon as possible thereafter. Our group and research
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or energy-efficient mission execution. Similarly, advanced control algorithms depend on reliable sensor integration and accurate dynamic models of the vehicle and propulsion system. The PhD project will
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in general. You are very well-versed working with data, models, statistics, simulations, and in general quantitative methods. Basic experience with programming (e.g. python) is a requirement, while
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Sciences at Aarhus University invites applications with experience in 3D modelling and manufacturing technology, preferably within the dental field as per 1 October 2026 or as soon as possible thereafter
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with the energy systems simulation model, especially EnergyPLAN, would be a key qualification for the position. You also have experience working with urban, municipal and regional climate and energy