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Field
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complex behaviours, including learning, in the small invertebrate model organism C. elegans. We have recently discovered a range of novel dopamine receptors in C. elegans and found that different receptors
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(e.g., transportation networks, manufacturing systems, and truck routing). Assessing the relevance of the intake fraction (i.e., exposure efficiency) of major emission sources as a critical metric for
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processing, information and communication theory, machine learning, complex networks, and optimization. The employment This employment is a temporary contract of two years with the possibility of extension up
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(e.g., transportation networks, manufacturing systems, and truck routing). Assessing the relevance of the intake fraction (i.e., exposure efficiency) of major emission sources as a critical metric for
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to grow by 20% by 2030, these challenges require a shift from isolated logistics operations to collaborative, connected logistics networks. Upcoming policy measures, including kilometre chargers, CO2 caps
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systems (ITS). In particular, the successful candidate will conduct cutting-edge research in: Developing physics-informed neural networks (PINNs) for complex dynamical systems modeling and observer design
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will contribute to the development of novel concepts and proposal writing, while efficiently addressing complex challenges. Responsibilities will include writing reports, authoring publications, drafting
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chain network analysis and geospatial modeling. The successful candidate will have strong data science skills, including experience working with large, complex data from varied sources, and machine
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on applications to complex, dynamic systems. Design and simulate feedback control algorithms for thermo-mechanical systems and related applications. Collaborate with faculty and student teams to support control
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healthcare applications. We use large real-world complex datasets, including data extracted from electronic health records and medical images, for applications pertaining to patient diagnostics and prognostics