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Field
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The development of integrated CO₂ capture and conversion as a cornerstone of the net-zero transition is driven by ambitious goals and targets set by the European Commission, among others, under
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for medical imaging, tailored for deep learning. The high-level goal of the project is simple: to use anatomical knowledge and existing knowledge as training data for deep neural networks (instead of manual
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, whilst also setting the foundations for the software technologies to run on this new generation of equipment – which of course includes AI. Meanwhile we are pushing the limits of applied mathematics
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proteins in the mixture together define the key properties of these systems. Predicting these properties by only studying their components might seem impossible... but that is what we aim to do in the Big
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://romeijn.web.rug.nl/paper/2023_romeijn_-_VICI_project_description.pdf ), where you can find a detailed list of planned PhD and postdoc positions. Candidates can freely choose their research topic within the domain
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with several PhD students, postdocs and staff members. You will be working on a combination of topics in a collaborative environment, including cell biology, muscle physiology and exercise physiology
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mechanisms during DNA replication. By integrating defined DNA templates, biochemical assays, and mass spectrometry, we will uncover how these structures are detected and processed, and what consequences
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ageing but is rare in wild populations. We will analyse longitudinal changes in social networks and biological age (using an epigenetic clock) within individuals to reveal the effect of social stress
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processes are important for the delivery of soil functions in these farms and how management practices shape these processes. Your work will help define potential soil indicators for success in the transition
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. The high-level goal of the project is simple: to use anatomical knowledge and existing knowledge as training data for deep neural networks (instead of manual annotations). The research will be conducted