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Group Leader and Professor AI in Biology - Dept of Computer Science and Dept. Electrical Engineering
but are not limited to: development of new AI architectures for biology and hybrid models that combine deep learning with mechanistic models; foundation models of genome regulation using single-cell and
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hedonic and causal machine learning models, to estimate the impact of renewables on house values. We will work closely with a range of stakeholder groups to tailor outputs in ways which maximise their value
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/nanoplastics, and other environmental compounds to assess their potential impacts on human health and the environment using machine learning (ML), deep learning (DL), and big data analytics. His lab is
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computational models and machine learning methods, as well as experience in repertoire data analysis. Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR8023-CLAMAR-001/Default.aspx Work
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of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI implementation. Ability to apply AI to interdisciplinary research or developing AI models
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experimental studies, mechanistic modelling, time-resolved data analysis, and machine learning to develop and validate predictive models linking process signals to reaction behaviour, progressing from controlled
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Engineering, we are seeking a researcher with a strong interest in developing and applying machine‑learning methods for materials design, in particular steel design. The position is part of our growing research
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operations across multiple departments. Transforms manual processes into AI-driven solutions, focusing on building robust data pipelines, creating efficient machine learning models, and integrating AI
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adaptive cybersecurity solutions for shared social and economic systems. The successful researcher will apply expertise in programmable networking, network traffic analysis, and machine-learning
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. The postdoctoral researcher(s) will join an international research environment at Umeå University, including Stat4Reg (www.stat4reg.se ), which develops statistical and machine-learning methods for register data