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technological progress in our increasingly digital, data- and algorithm-driven world. Integreat develops theories, methods, models, and algorithms that integrate general and domainspecific knowledge with data
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to Neuroimmunology and Multiple Sclerosis. Our department provides translational science expertise to inform the clinical development of novel personalized therapeutics, and our biomarker teams investigate
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algorithms, including machine unlearning techniques, to enhance model robustness and reliability. Design and execute rigorous AI testing frameworks to assess and mitigate risks in AI systems. Collaborate with
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algorithms, including machine unlearning techniques, to enhance model robustness and reliability. Design and execute rigorous AI testing frameworks to assess and mitigate risks in AI systems. Collaborate with
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not limited to using UAV platforms to characterize active fire thermal and gas emissions, improve spreading models and detection algorithms, and assessing post-fire effects. The aim of the project is to
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research that covers the energy value chain from generation to innovative end-use solutions, motivated by industrialisation and deployment. ERI@N has multiple Interdisciplinary Research Programmes which
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the mathematical and computational engine of Artificial Intelligence (AI), and therefore it is a fundamental force of technological progress in our increasingly digital, data- and algorithm-driven world
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at the intersection of neuroscience and AI, with opportunities for innovation and collaboration across multiple disciplines. Candidates are expected to have experience in cutting edge AI technologies and their
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algorithms. The candidate should have the following skills: • Strong technical, analytical, and quantitative abilities; • Strong interpersonal, organizational, and communication skills, and the willingness
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microscopy. The ideal candidate will be highly creative, hardworking, and a team player. They will also have the ability to manage multiple projects and students in pursuit of team goals. Representative