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-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven models for complex data, including high
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computational costs by orders of magnitude and enabling breakthroughs in drug design and materials science. The position bridges machine learning and molecular science, with opportunities for collaboration
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results into practical applications for end users. Subject Description The research aims to develop machine learning models for microbe detection, focusing on the mathematical foundations in geometry and
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description The postdoctoral project is focused on development and the exploitation of machine learning tools to accelerate the analysis of microtomography data at the MAXIV synchrotron facility. MAXIV
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We are seeking a highly motivated and skilled Postdoctoral researcher with interdisciplinary expertise to develop risk assessment and mitigation models using Large Language Models (LLMs
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learning can improve software architecture recovery, how to optimize machine learning models at compile and runtime, and autonomous agents for software development. Part of the research is conducted through
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new methods incorporating transformer models, graph neural networks, and self-supervised learning approaches that can extract deeper biological insights from genomic data. Join us in this exciting
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of Molecular Mechanisms and Machines, (IMOL), Poland, and the Leicester Institute of Structural and Chemical Biology, United Kingdom. More information about the total announced post-doctoral positions within in
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systems, and machine learning. While the initial focus of the position is on this project, we offer significant opportunity for the applicant to develop their own independent research trajectory in
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include the design and implementation of finite element multiscale models and machine learning algorithms, analyzing related experimental data, and collaborating with industrial collaborators to validate