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Field
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metrics for reducing the environmental impact of AI and cloud computing Empirically evaluate different parts of the AI lifecycle, including development (training), operation (inference) and use Develop
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to: Identify and evaluate carbon metrics for reducing the environmental impact of AI and cloud computing Empirically evaluate different parts of the AI lifecycle, including development (training
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Title: Postdoctoral Research Associate: High Performance Cloud Computing Laboratory (HPCC Lab) Employee Classification: Postdoctoral Research Assoc Campus: University of North Texas Division: UNT
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through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description In large-scale systems such as clouds
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Medical School. In August 2024, we welcomed our first intake of the NTU MBBS programme, that has been recently enhanced to include themes like precision medicine and Artificial Intelligence (AI) in
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with cloud-based computing platforms (AWS, Azure, Google Cloud) and high-performance computing (HPC) environments. Understanding of data privacy, security, and ethical considerations in handling clinical
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Maximize the use of hardware resources, including local hardware, cloud platforms (VMs, Cloud Buckets) and compute clusters (SLURM). • Research Support & Collaboration: o Reproduce existing deep
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programming, statistics, computational analysis and if possible environmental awareness. • Prior experience working with LiDAR or point cloud data will be a definite bonus. • Excellent project management
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full-time position, annual leave 36 days well equipped facilities, the tools required for research: computer farms and cloud computing infrastructure, software, servers, etc. work in active an inspiring
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detection. Familiarity with real-time applications of AI/ML in embedded or IoT devices. Knowledge of cloud-based computing platforms for data processing (e.g., AWS, Google Cloud). Understanding of BMS