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public health. In this role, you will develop and evaluate novel AI and machine learning methods using large-scale multimodal datasets, contributing to epidemiology-informed foundation models, predictive
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are particularly interested in how alterations to ENS macrophages in aging and neurodegenerative diseases contribute to disruption of gastrointestinal motility. We use well-established mouse models and human gut
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, biomedical data science, digital health, epidemiology, and environmental health. The position focuses on the development, validation, and interpretation of AI models for health risk prediction using
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/or quantum material systems. A PhD in chemical engineering, chemistry, material science, physics, engineering or related field is required, along with a proven track record of conducting and publishing
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postdoc, you will contribute to research and teaching within advanced modelling, optimization and design of composite and lightweight structures for applications such as wind turbine blades. Your work tasks
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are still not exploited to their full potential. The CROPWAVES project aims to contribute to better future food security by improving global-scale crop and climate models through the integration of satellite
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As a postdoctoral researcher, your primary responsibilities will be: Develop machine learning and deep learning models, with a strong focus on computer vision, for the characterisation and
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techniques: identifying the factors that establish early RT at target genes, determining how they promote translocation biogenesis, and testing them in preclinical models. The work combines CRISPR engineering
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scales. We integrate paleomagnetism and rock magnetism with field geology, structural geology, tectonics, geophysics and geodynamic modelling to address plate-boundary evolution, lithospheric deformation
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scales from microchannels to full rack systems (5.) Develop physics and AI-based models to elucidate physics, perform optimization, and create surrogate models for system level simulators (6.) Participate