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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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: 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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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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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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Elgammal, Bingchen Liu, Mohamed Elhoseiny, and Marian Mazzone, CAN: Creative Adversarial Networks, International Conference on Computational Creativity(ICCC), 2017 Theme B continual learning (selected papers
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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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-class students, faculty, and researchers from over 100 nationalities. The result is a network of talent that enables radically dierent perspectives. With holistic support for creative minds and unmatched
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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