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, sensors and instrumentation. Knowledge of one or more of the following areas:Power electronics, Reliability and failure mechanisms, Sensors and instrumentation, Data analytics, machine learning, or AI
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logging and/or testing of samples; routine animal husbandry and experimentation, and genotyping May occasionally instruct others in basic laboratory techniques or procedures; Performs related laboratory
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multi-omics integration with advanced machine learning, including artificial neural networks, to predict disease-relevant splice variants across cardiometabolic diseases. By leveraging extensive meta
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industry and academia together to drive pre-competitive, fundamental research in polymers. We welcome applicants with interests in polymer physics, materials processing and characterisation, machine learning
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econometric and machine learning frameworks to analyse the causal relationships between transport behaviour, residential energy consumption, and environmental outcomes in urban systems. The successful candidate
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Familiarity with spatial analysis, GIS, or geospatial data workflows. Experience with machine learning, modelling, or systems analysis approaches Interest in resilience, sustainability, and environmental
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research experience in e-health, digital health or a related field experience of, or a documented interest in, machine learning, AI methods or large language models (LLMs) in clinical or health-related
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mechanisms, Sensors and instrumentation, Data analytics, machine learning, or AI, Digital twins or physics-based modeling, wide-bandgap semiconductor technologies. Excellent written and spoken English
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the AIM-PACE project, which aims at developing a new generation of safe-and-sustainable-by-design, bio-based and circular plastics by combining AI, microbial technology, computer modelling, and polymer
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mechanisms occurring in these materials and their synthesis over all relevant length scales (e.g., cutting-edge ab initio methods, atomistic simulation methods, multi-scale modelling, machine learning) High