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candidates whose expertise falls within one or more of the following areas: computational and mathematical modeling, statistical modeling, machine learning, network science, bioinformatics, applied mathematics
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data and multimodal datasets combining imaging and molecular measurements. Have a background in computational biology, bioinformatics, or machine learning for biological problems. Have experience with
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, and managing multimodal datasets including physiological, movement, environmental, voice, and self-reported data. Contribute to the development and evaluation of machine learning models for physical and
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description Work on EU projects to develop next‑generation transport, emission and health forecasting models by integrating deep learning, xAI, and diverse data sources such as traffic sensors, smart‑card data
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spans computational materials design, catalysis, energy materials, machine learning, and artificial intelligence. We offer a collaborative and international research environment with close interactions
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. The following experience will strengthen your application: industrial product development or manufacturing research modelling and simulation, digital twins or digital threads AI, machine learning
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measurements. Have a background in computational biology, bioinformatics, or machine learning for biological problems. Have experience with modern deep learning frameworks (PyTorch, JAX, or equivalent). Have
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Qualifications The following qualifications and experience will be considered an advantage: Experience with crop modeling. Experience with plant breeding. Background in data science, machine learning, and
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qualifications: Coursework or thesis work in complex systems, network science, agent-based modelling, transport modelling, urban analytics, resilience, computational social science, data science, machine learning
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learning research. What you will do Propose, develop, and evaluate advanced machine learning models, including reinforcement learning methods, for the energy-aware coordination of EV fleets. Publish high