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flow, fluid dynamics, and sustainable energy systems. The research focuses on developing new methods to study and model multiphase flows as key phenomena in energy and industrial processes. The work
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14 DCs in cutting-edge methods, theory, and transferable skills. More information may be found on the ENERPOL home page at https://cordis.europa.eu/project/id/101226229 . The part of the project
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attitude to share information. In addition, you will participate in analysing and interpreting different type of data. You are expecting to have the responsibilities of developing methods for analysing and
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description Trustworthy machine learning is an umbrella term that provides methods and tools to ensure that AI and ML systems are verifiable, robust, secure, privacy-preserving, and ethical, which leads
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on developing a fundamental understanding and numerical models for multiphase flows, which are crucial for various industrial processes. The successful candidate will develop advanced physics-based methods in
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to study gene function in malaria parasites. The PhD student will apply scalable and innovative analytical methods to characterize the role of parasite genes during replication and host interactions
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treatment method. We conduct research across a broad range of areas, including trauma, degenerative disease, pediatric orthopedics, and hand surgery. Depending on the research question, we employ a wide
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to avoid becoming obsolete before they are decommissioned. By studying and developing knowledge in post-quantum cryptography, existing methods against post-quantum attacks are improved, which in turn ensures
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Description: We are looking for a motivated and committed PhD student who wants to understand the genetic consequences of modern breeding of farm animals and to develop the genomic breeding methods
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of farm animals and to develop the genomic breeding methods of the future. The position involves doctoral studies where you will analyze genomic data, develop new models and simulations, and present new