2,400 model-driven-development "Integreat Norwegian Centre for Knowledge driven Machine Learning" PhD positions
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, The Netherlands. ENTEG research is highly multidisciplinary in nature and focuses on fundamental and applied research on the development of new and innovative processes and products for a wide range of product
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The candidate will develop and benchmark zero-shot multimodal fusion models for rare disease prediction, using melanoma as a use case. The project integrates spatial and single-cell multi-omics data with
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AI-driven quantitative analysis and predictive modelling of biomaterials, tissues, and regenerative constructs. The project combines advanced 2D and 3D bioimaging, including micro/nanoCT, confocal
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UiO/Anders Lien 20th October 2026 Languages English English English Join the University of Oslo for a PhD in Biomaterials! PhD Position – AI-Driven Multimodal Analysis and Predictive Modelling
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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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generative models of how human tissues develop, mature and regenerate, and of what goes wrong in disease, with a focus on child health. The group starts in January 2027. You will develop generative models
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Your position You will develop generative models on single-cell and spatial genomics data, from sequencing and imaging, and apply them to human developmental and disease biology. Possible research
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what you will do Develop AI-driven mechanistic computational models of Non-Hodgkin lymphomas such as mantle cell lymphoma (MCL), diffuse large B-cell lymphoma (DLBCL), and Richter syndrome. You will
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share the goal of developing stable and reliable perovskite-based tandem photovoltaics, while maintaining complementary scientific responsibilities. FZJ focus: automated and data-driven development
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reservoir heterogeneity. This project will integrate core observations, wireline logs and seismic data to develop geological and petrophysical models that constrain reactive reservoir simulations