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derived use cases by focusing on one or more of the following topics in their PhD project: Training and inference of ML models on GPU clusters. Method development for scalable and green AI. Use cases in
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implemented in the Fortran programming language, and it relies on the platform CUDA for parallelization of the computation over several GPUs’ cores, and has interfaces with Matlab and Python for ease of use
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of code to utilize GPU-acceleration on DTU’s high-performance computing cluster or other HPC systems. You will also analyze realistic physical implementations of the architectures you explore, with a
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. The Center has state of the art equipment within DNA and RNA sequencing, laboratory automation, CPU and GPU compute resources, proteomics, metabolomics, and advanced microscopy. This position offers
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quantitative genetics, machine learning, bioinformatics, and population genetics, and their applications in an agricultural setting A modern dedicated computational infrastructure (CPUs & GPUs) Well-developed in
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on the platform CUDA for parallelization of the computation over several GPUs’ cores, and has interfaces with Matlab and Python for ease of use. However, powerful as it is, MagTense is at present limited in its
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electricity prices with focus on Nordic electricity market including implementation, test and validation at the DTU Risø HPP facility (possibly in a GPU computing infrastructure) Aid the implementation of IEA
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be direct access to advanced biophysical infrastructure in the biophysics core facility headed by the PI, a GPU cluster with working pipelines for computational design and the department’s bioimaging