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related topic and need to have expertise in working with data from the National Drug Treatment Monitoring System (NDTMS), working with government and expertise in quantitative prediction modelling
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) for predictive modeling. Collaborate with neuroscientists, biostatisticians, and clinical researchers within BBRC and external partners. Contribute to manuscript preparation, presentations, and dissemination
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, the Engineer will architect, engineer, and deploy AI pipelines that push technological boundaries for our clients. The Engineer will tackle complex challenges at the intersection of Large Language Models
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? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Development of advanced CFD models in OpenFOAM for the simulation of next
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and observation models to reflect real-time changes in environmental conditions, enabling more accurate predictions of adaptation impacts and thereby supporting a better-informed, resilient decision
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will contribute to the development of a new simulation-based pre-training framework for building more robust and trustworthy machine learning-based clinical prediction models. Funded by the Medical
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monitoring. • Develop numerical models to simulate the dynamic behavior of mooring and anchoring systems under different environmental conditions. • Analyze and optimize structural performance and predictive
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effectiveness and toxicity of the treatments. Other duties: Develop and validate cancer risk prediction models using deep neural networks based on semistructured data. Develop and validate learning strategies
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of whole plants at crop level. A central element is the plant’s 3D geometry, and models should predict plant growth, development, and yield as well as key physiological relationships across the whole plant
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is to move beyond traditional “check-after” approaches and instead predict and prevent errors while the radiotherapy treatment is being delivered. The candidate will build upon this existing prototype