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learning, with experience in time series forecasting or related applications. You have experience with or a strong interest in graph neural networks, Bayesian methods or uncertainty quantification techniques
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test prototypes. With the consortium, we investigate assembly, disassembly, repairability, and user experience in an operational environment. Building on this case, we develop the methodologies enabling
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results through numerical experiments. You will conduct your research in a collaborative, international, and interdisciplinary environment that values both academic excellence and open exchange of ideas
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Computer Science, Software Engineering, or Artificial Intelligence. You have strong programming skills and experience in developing AI solutions and real-time simulation platforms. You have strong written and spoken
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Intelligence, Applied Mathematics, Electrical Engineering, or a closely related field. You have demonstrated expertise in machine learning and deep learning, with experience in time series forecasting or related
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engineering or similar field Experience in microfluidics, specifically segmented slug flow Programming proficiency, preferred in python and LabView Interest in the field of metabolomics, programming, and NMR is
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assays to assess nuclease activity, stability, and specificity; maintain plasmid libraries, strain collections, and detailed experimental records; collaborate with researchers across WUR and contribute
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Information Science (GISc) — particularly in movement analysis — with teaching and student supervision? Have you recently earned a PhD in GISc and feel inspired to share your expertise with the next generation while
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at the laboratory of Food Process Engineering, you will play a pivotal role in the EU Future Foods project. You will bridge experimental and modelling results in order to arrive at microfluidic device that can be
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qualitative research skills, policy analysis experience, and experience working in different One Health settings abroad. Your duties and responsibilities include: Contribute to the BIORESIST study by evaluating