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this project, you will develop new image analysis methodologies for less invasive and non-invasive quantitative brain PET studies using LAFOV PET/CT. You will work on model-independent kinetic analysis methods
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devices, building a software-supported framework to predict and optimize laser-material interactions, energy transfer, and resulting micro-scaled features during drilling and shaping, and modelling of beam
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to join a multidisciplinary biomedical research team. The successful candidate will contribute to cutting-edge research involving genome engineering, transgenic animal model development, molecular biology
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of interest, e.g. the spectral density of strongly correlated models, as measured in ARPES. • The mathematics of the approach will require a lot of innovative developments too. In the only published article
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: Advancing machine unlearning, privacy-preserving techniques, and robust data curation. AI Safety: Ensuring robust alignment and safety in multi-agent LLM systems Efficiency: Streamlining large-scale model
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biology, molecular biology and animal models to investigate how these hybrid cells favour carcinogenesis. Where to apply Website https://app.smartsheet.au/b/form/019eedeef91978fdbc2b67718479eac6?project_id
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Inria, the French national research institute for the digital sciences | Saclay, le de France | France | 3 months ago
with language models (e.g., ChatGPT). More recently, AI has begun to be applied to scientific and engineering problems. Its goal is to create an "augmented engineer" who can carry out studies and make
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of the molecular and cellular events that lead to vascular calcification in chronic kidney disease. Animal models for chronic kidney disease or diabetic mice will be performed to mimic human relevant diseases. By
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. The work will progress from well-defined model minerals to recycled and secondary mineral resources with the support of the supervisors and project consortium. The position includes the following
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Thermal Conversion and Storage group at the University of Twente, you will investigate CO₂ desublimation under controlled cryogenic conditions. The project is primarily experimental, supported by modelling