2,426 model-driven-development "Integreat Norwegian Centre for Knowledge driven Machine Learning" PhD positions
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cardiovascular disease. A possible direction for the work is the development of probabilistic graphical models that represent proteins as latent causal drivers of disease, while treating other omics layers as
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PhD in Advanced Testing, Modelling, and Simulation of Composite Materials under High Velocity Impact
impacts. The candidate will develop and validate computational models capable of predicting penetration, damage evolution, and energy absorption, while exploring novel lightweight material configurations
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to develop and utilize innovative, interpretable data-driven analysis methods to significantly advance our understanding of immune cell inter-relations within the cancer microenvironment. We will apply
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Mechanical Interaction (PCMI) Benchmark’ exercises. Based upon the validation exercise, highlight areas of future code development, including routes to modelling postulated idealised loss-of coolant accidents
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under future climate and fishing scenarios. What are you going to do? You will develop stage‑structured population models for both species, explicitly including life‑history processes, sea‑ice dependence
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is the development of hybrid models that combine our integrated national model of Denmark with AI-based methods to improve predictions of floods and droughts. We seek to enhance our ability to predict
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Fully Funded PhD Studentship (Home Fees) Project Title: Developing Fair and Robust Cancer Risk Prediction Models Using Health Data Supervisor: Professor Angela Wood (Professor of Biostatistics and
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protection benefits provided by restored saltmarshes. The successful PhD candidate will work with laboratory experiments and develop numerical and AI models capable of supporting coastal management and
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Job related to staff position within a Research Infrastructure? No Offer Description The student is expected to work on novel methods for reasoning in large multimodal models, with a focus on enabling
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profiles, language proficiency and accent familiarity Exploring how AI, speech models and large language models can support prediction of comprehension and listening effort Developing validated models and