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project, we are looking for a strong candidate to contribute to the development of quantum algorithms and applications, focusing on quantum walks and quantum machine learning on graph structures. Your
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research aims to develop new AI for shared human-AI decision-making in healthcare imaging. This post focuses on bridging theory and applications of the Learning-to-Defer (L2D) framework, building on recent
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to accelerate biomedical discovery. Our mission is to transform bold scientific ideas into advances that improve human health. In this context, the Funke lab develops machine learning methods to accelerate
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15 Apr 2026 Job Information Organisation/Company Graz University of Technology Department Institute of Machine Learning and Neural Computation Research Field Computer science Researcher Profile
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-generation AI models of gene regulation and disease progression. Our work is redefining Parkinson’s disease biology and enabling translational breakthroughs. The role Develop deep learning models across genome
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developing cutting edge analytic tools for studying the genome transformation and genomic activities. 70% - The candidate will be mainly focusing on developing machine learning methods and/or AI algorithms
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user and stakeholder engagement. The candidate will be embedded in a multidisciplinary research environment combining expertise in machine learning (ML), numerical modelling, satellite remote sensing
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argumentative agentic AI approach for chemical development settings based on reinforcement learning but able to shape rewards with the help of ontological knowledge as well as expert knowledge from humans and
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 8 days ago
methodology, machine learning, and biomedical data science. Our research develops rigorous and interpretable methods for high-dimensional biomedical data, with applications spanning cancer genomics
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the groups of Dr Joe Forth, Dr Anthony Bradley, and Project Lead Professor Steve Rannard, applying your expertise in machine learning, cheminformatics, and soft materials to accelerate LAT design and