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positions in the interdisciplinary research environment “Culture and Society” to develop research on themes relevant to the thematic area “Digital Society, Infrastructure, Legacies”. This thematic area
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of this PhD project is to develop machine learning algorithms that perform efficiently and coherently across both classical and quantum computing platforms. The PhD project falls under the collaboration between
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methods that reduce compute, energy usage, memory and storage demands, and associated carbon emissions while aiming to maintain model quality. Your work will include developing new methodologies and
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, computer science, and statistics The objective of this PhD project is to develop machine learning algorithms that perform efficiently and coherently across both classical and quantum computing platforms. The PhD
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functional theory. In collaboration with Phasecraft, a leading quantum algorithms company, this project will explore the generation of new quantum computing datasets and the development of machine learning
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the context of critical illness. This position focuses on computational modeling of host-response mechanisms using high-dimensional multi-omics datasets. The fellow develops novel computational pipelines
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digital health and multi-agentic coordination. This role requires the development of self-learning artificial intelligence models tailored for dynamic healthcare environments. The candidate designs and
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solutions using first motion. Experience in full waveform inversion using innovative tools (e.g. ISOLA) and methods (ML), earthquake location algorithms, computer programming and geophysical equipment
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Requisition Id 15854 Overview: We are seeking a research professional with fundamental knowledge in artificial intelligence (AI) who will focus on developing and applying AI algorithms to signal
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of Health Informatics as part of a group of over 30 researchers using clinical data to improve our understanding of disease and the effectiveness of treatments, and implementing AI algorithms to deliver safer