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interdisciplinary research across AI hardware, software, and algorithms. AI Accelerators, ML Algorithms, AI Frameworks, and Model-System Codesign have been focus areas in the past - we are always excited to sponsor
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Project link: Next-Generation Farrington Model for Infection Prevention and Control: An Enhanced Farrington Algorithm with Spatiotemporal and Adaptive Baseline Capa | Project Opportunities | PhD
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, Purpose of the Job We are looking for one Research Associate to work on the development, implementation and testing of predictive control algorithms for the optimal coordination of available multi-energy
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Data teams of NQCP. Role Description We are looking for an experienced quantum systems modelling profile to help drive our efforts in the development of digital twins of quantum devices. In this role
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on the project of NEMO Sub-Project C: Passive UE activity inference (4/5G) from OTA network traffic. The role will focus on developing algorithms and methods for processing and analyzing 5G signals. We
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research in MAE addresses the immediate needs of our industries and supports the nation’s long-term development strategies. In the new era of industrial 4.0 and sustainable living, MAE is rigorous in
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an important role in the development and deployment of research-related, computational tools used in the analysis of bacterial genomes, and the biological interpretation, contextualization and reporting
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postdoctoral researcher with a strong background in sequence bioinformatics, algorithms and data structures. The successful candidate will join an interdisciplinary effort developing innovative diagnostic
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- Experience in academic research - Knowledge of software development: Linux, Git - Expertise in algorithm design and analysis - Excellent science communication skills Desirable skills, knowledge and experience
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and engineers on developing resource-efficient, adaptive learning frameworks for complex data environments. Key Responsibilities: Design and implement ensemble learning algorithms and optimization