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The aim of this project is to describe ion conduction and activation/inactivation processes by employing molecular dynamics and statistical mechanical methods. The expected outcome is an improved
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the fields of cloud computing, computer networking and immersive systems to develop elastic and cost-efficient cloud-based AI pipeline to tackle climate change and support sustainability. Some of the tasks
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the fields of cloud computing, computer networking and immersive systems to develop elastic and cost-efficient cloud-based AI pipeline to tackle climate change and support sustainability. Some of the tasks
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quantitative methods. Expected outcomes include new knowledge on designing for technology-supported wellbeing, particularly when using human-centred AI. The project will involve critical analysis of existing
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data requirements, and lower costs for large-scale modelling tasks. PINNs enhance predictive capabilities and efficiency by combining data-driven methods with physical principles. Unlike traditional
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One fully funded, full-time PhD position to work with Prof. Mahesh Marina in the Networked Systems Research Group at the School of Informatics, University of Edinburgh. The broad aim
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The Institute for Infection Prevention and Control (IPC, Head Prof. Dr. Philipp Henneke) is looking as soon as possible for a Bioinformatician (m/f/d, PhD) with focus on the analysis of large
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. Strong interest in advanced neurofunctional assessments and methods (e.g., computer vision, bioacoustics, machine learning/AI, neuroimaging, eye-tracking, multimodal data fusion) and/ or willingness
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prospective sustainability assessments of pharmaceutical manufacturing via data-driven and hybrid methods. The PhD student will be appointed within the framework of the European project PHARMECO (Advancing Safe
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structural diagnostics for the system. The work will be performed in the group of Prof. Christos Likos at the University of Vienna in collaboration with the experimental group of Dr. Emmanuel Stiakakis