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Field
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, FEDER and FCT, is available under the following conditions: OBJECTIVES | FUNCTIONS Cloud computing is currently in an impasse. While hardware efficiency is improving at an exponentially lower rate, the
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project deliverables are met. Derivation of closed-form theoretical latency and timeliness expressions for cloud-hosted AI services and edge-assisted offloading strategies. Analysis of theoretical latency
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for cloud-hosted AI services and edge-assisted offloading strategies. Analysis of theoretical latency and timeliness for cloud-hosted AI services and edge-assisted offloading strategies. Design and
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TEC. 2. OBJECTIVES: - broaden knowledge of the state of the art in the scientific field of DevOps Cloud Architectures, Infrastructure as Code (IaC) and on-demand, intelligent configuration of self
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bioinformatics tools and libraries (e.g., Bioconductor, STAR, DESeq2, Seurat) and familiarity with cloud computing platforms and scalable computing infrastructures for large datasets. How to Apply: Interested
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analysing of point cloud data mainly from airborne LiDAR (ALS) but potentially also from terrestrial and mobile sources (TLS & MLS). The goal of the project is to uncover the efficacy of using airborne LiDAR
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security mechanisms connected to the cloud in residential environments and intrusion detection methods in the context of embedded systems and IoT devices. The work will explore machine learning techniques
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for improved interpretability and generalization. Familiarity with high-performance computing (HPC), cloud platforms, or GPU clusters. Demonstrated ability to work collaboratively in interdisciplinary and cross
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and Machine Learning tools and algorithms to solve hydrology and water resources problems. Familiarity with high-performance computing (HPC), cloud platforms, or GPU clusters. Demonstrated ability
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algorithms to solve hydrology and water resources problems. Familiarity with high-performance computing (HPC), cloud platforms, or GPU clusters. Demonstrated ability to work collaboratively with