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of equity, diversity and inclusion. Desirable characteristics: Experience in large data sets and their platforms/tools, cloud-based architectures, and deployment frameworks for machine learning algorithms
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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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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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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
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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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-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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access to numerous cultural, recreational, and outdoor opportunities. The Horticulture and Landscape Architecture department strives to discover, apply, and disseminate knowledge and technology while
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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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, software development, and research experiments. Contribute to the development of working prototypes and demonstrations for mobile biometric systems utilizing federated learning architectures. Prepare
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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