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Field
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precision medicine based on gene sequencing time series data. Large data sets come with significant computational challenges. Tremendous algorithmic progress has been made in machine learning and related
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within the Norwegian Center on AI for Decision (aiD), benefiting from broad and divers expertise, and strong industrial connections. The project will have theoretical and algorithmic developments, software
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will develop and evaluate fault detection and fault location algorithms for these systems. The project is funded by GE Vernova under a wider collaboration with Imperial College London. You will be co
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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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, to create a responsible and innovative university to serve as a model for the 21st century. Within ICN, the ChemSenSim group (https://lab.chemsensim.fr/ ) develops interdisciplinary research projects
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of promising nanoagents. The objective of this doctoral project is to develop an innovative method for sensing and quantifying the hotspot effect in aqueous suspensions of optically absorbing nanoagents, without
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nuclear and particle physics research leveraging machine learning and AI for data analysis and detector development, as well as exploratory work in quantum algorithms, depending on background and interests
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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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algorithms for microscopy image analysis problems (primarily 2D timelapse data), which are driven by real applications in life science research Developing solutions to integrate large foundation models
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transmitters, DPD algorithms, and analog/mixed-signal challenges. For more details about the DISRUPT project, please visit: https://elca.tudelft.nl/Research/project.php?id=243 https://www.linkedin.com/posts/tu