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Field
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-of-the-art neuromorphic compute architectures. Collaborate with the neuroscience, engineering, and computer science RAs to develop demonstrator applications, and to conduct research, publish, and disseminate
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the architecture of multi-trophic ecological interaction networks to the impacts of invasive plant species on ecosystem multifunctionality to inform approaches for ecological restoration. The ideal candidate will
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advanced communication technologies (e.g., 5G) for industrial automation and remote operations. Desirable: Experience with open process control architectures. Familiarity with advanced communication
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, which means the thesis must be submitted by the role’s starting date) in an appropriate field (e.g. architecture, civil engineering, energy, energy in buildings, community energy). PhD equivalence is
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architectural or landscape construction. Current research projects include: (1) Material-led Mechanisms—exploring living and bio-materials as modifiers for bio-fabrication in construction; (2) Performative
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circuit modeling, simulation, and layout design techniques. Proficiency with using relevant tools such as ADS, HFSS, Cadence and Matlab etc. Familiarity with RF/mm-wave transceiver architectures and
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-MS, XL-MS) Background in aging research or neurodegenerative disease models Knowledge of exposome research methodologies Familiarity with or desire to learn neural network architectures for biological
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architectures, and interpretable AI methods and libraries, concept-bottleneck architectures, attribution packages: shap, captum, etc. Experience with bulk and/or single-cell omics data analysis (e.g. bulk
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Qualifications Research experience with unsupervised and weakly supervised CNN and RNN architectures such as GANs, contrastive Learning, multiple instance learning, and transformer models Experience with
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implementation Knowledge of networking protocols and architectures PhD or equivalent R&D experience in computer science, networks or communications, and/or experience with at least one of the following areas