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models (e.g., CNNs, diffusion models, etc) Proficiency in Python Experience with HPC (CPU or GPU, with GPUs preferred) Related Skills and Other Requirements Ability to collaborate on the application of AI
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Physics , Non-equilibrium many-body theory , Superconductivity Appl Deadline: (posted 2024/10/10, listed until 2025/06/01) Position Description: Apply Position Description Applications are invited to a
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libraries for modern architectures (e.g., GPUs). Exploration of linear algebra methods in computational physics applications and machine learning. Integrate and benchmark the GINGKO library, a sparse solver
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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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training in the second area are encouraged to highlight this in their application. Experience with high performance computing and GPU acceleration tools (e.g. CUDA) and deep learning frameworks, such as
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FWO-UGent funded bioinformatics postdocs: Unveiling the significance of gene loss in plant evolution
environment Access to state-of-the-art tools and computational infrastructure, including CPU/GPU clusters Opportunity to contribute to cutting-edge research in plant evolution and genomics Support
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++ and Python programming languages. Experience in open source projects, GPU programming, distributed computing and cloud computing are considered to be strong assets. The position of Research Fellow at
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. Please indicate in your application which of the above listed projects is most intriguing for you. Your profile Eligible candidates have strong skills in computational molecular (bio)physics, statistical
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details about the project will be provided for short-listed candidates. Your profile The project will involve both experimental and computational work and the candidate is expected to be comfortable with
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details about the project will be provided for short-listed candidates. Your profile The project will involve both experimental and computational work and the candidate is expected to be comfortable with