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Field
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projects typically move into influential roles in data-driven engineering, infrastructure resilience, environmental risk analysis, or directly into Network Rail’s technical and analytical teams. Because
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Your Job: You will participate in an international team in an EU-funded Doctoral Network project called MINDnet. The project consists of 15 PhD students at 7 universities, one research center and
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and data analysis Your Profile Master's degree in chemistry, physics, or related fields Excellent communication skills and ability to work in a team are essential Very good command of written and spoken
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analytics methods for the study of historical paintings in an interdisciplinary research environment. You will contribute to the development of state‑of‑the‑art methods that advance the analysis of complex
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e.g. Python/R. Desired experiences: Molecular laboratory, bacteriology and/or cultivation-based experimental work. Network-based analysis of multi-omics data. Molecular lab experience A PhD student with
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the use of hierarchical graph neural networks for modeling multi-scale urban energy systems. By combining advances in Physics-Informed Machine Learning (PIML) and Graph Neural Networks (GNNs) with real
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health, impact attribution, climate change, earth system modelling, environmental epidemiology, doctoral networks. Climate change poses growing risks to child health, particularly in Sub-Saharan Africa
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of denoising algorithms and incorporation into PET image reconstruction Data and image analysis. Writing scientific publications and participating in international conferences. Developing professional algorithm
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defining formulations with desired properties, (ii) in silico microbiome design based on systems biology network analysis, and (iii) in vitro validation in a (inhouse developed) biofilm bioreactor system
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as "world-leading" (4*) or "internationally excellent" (3*) and our research collaborations and networks extend nationally and internationally. Research undertaken at the School is relevant to both