16 network-coding-"Chung-Ang-University"-"Chung-Ang-University" positions at King Abdullah University of Science and Technology
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topics. Candidates should have some experience working with FPGAs as well as an understanding of computer networks. Experience with both RTL and HLS design is favoured. The ideal candidate would have some
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in a connected context, investigating how accelerators can be designed, integrated, and scaled for emerging large scale and networked applications. We are interested in new ways of virtualising
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, elevators, electrical networks (high and low current), building automation systems, and fire alarm systems. Key responsibilities include client interaction, coordination and supervision of maintenance
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Elhoseiny, Code: https://github.com/yli1/CLCL Uncertainty-guided Continual Learning with Bayesian Neural Networks (ICLR’20), Sayna Ebrahimi, Mohamed Elhoseiny, Trevor Darrell, Marcus Rohrbach, Code: https
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Serve as the Lead for the team ensuring smooth operation of the Linux cluster consisting of 300+ GPU/CPU compute nodes including parallel filesystems and high-performance network. This is partly
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: Docker, MLflow ○ Expertise in 2D/3D image segmentation, detection, and Stable Diffusion techniques (U-Net, V-Net, DeepLab) ○ Strong experience with Generative AI models (GANs, VAEs
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state-of-the-art genomic technologies. We ask fundamental questions on how cells operate as molecular machines with special reference to the dynamic gene regulatory networks governing cellular identity
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. This includes facies analysis, environmental research, diagenesis, pore-network analysis and stratigraphy. Additional ideas will also be considered. A multitude of data is already available including shallow
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of bioinformaticians, computer scientists, biotechnologists, biologists, and biochemists. The successful candidate will also enjoy an environment aimed to facilitate progress in the research career: networking, student
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and biostatistics, with expertise in mathematical and statistical modeling techniques including agent-based models, compartmental models, and network analysis. Previous experience in investigating