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Field
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programming proficiency in Python and C/C++. Expertise in ensemble learning (e.g., Random Forests, Gradient Boosting, bagging/stacking frameworks). Hands-on experience with parallel or GPU-based computing (CUDA
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independently, and solve complex problems, Desirable qualifications: Experience with Vision-Language(-Action) models or physics-informed ML. Experience with GPU programming, NVIDIA Omniverse, Isaac Sim, or other
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working in interdisciplinary teams Clear record of communicating original results in writing and presentations Desired Qualifications: Knowledge of GPU architecture and experience programming GPUs
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. Ability to succeed in an interdisciplinary team and communicate results clearly in writing and presentations. Desired Qualifications: Knowledge of GPU architecture and GPU programming. Interest
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communicate results clearly in writing and presentations. Desired Qualifications: Knowledge of GPU architecture and GPU programming. Interest or experience in distributed training on large scientific datasets
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/GPUs. These devices provide massive spatial parallelism and are well-suited for dataflow programming paradigms. However, optimizing and porting code efficiently to these architectures remains a key
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the computer science research conferences. Qualifications: PhD in computer science with file systems, GPU architecture experience. Proven ability to articulate research work and findings in peer-reviewed proceedings
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. The researcher(s) will be provided access to state-of-the-art supercomputing facilities with advanced GPU and data storage capabilities. Additionally, opportunities will be available for collaborations. Duties
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The EPAD project – Electron-Positron Attosecond Dynamics in Exotic Systems
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communication with a record of leading and reporting results. Desired Qualifications: Knowledge of quantum computing algorithms. Familiarity with tensor network methods. Experience programming GPUs. Experience