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HPC and GPU infrastructure, you will contribute to internationally leading research, publish in high-impact journals and present your work at major scientific conferences. About You You will be
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and high-performance or GPU-accelerated computing environments. Applying rigorous methods for external validation, transportability, subgroup performance, fairness, uncertainty quantification, and
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excellent infrastructure for deep learning, speech, and audio research, including Aalto University’s large-scale scientific computing cluster with CPU and GPU nodes, access to CSC’s national computing
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infrastructure for deep learning, speech, and audio research, including Aalto University’s large-scale scientific computing cluster with CPU and GPU nodes, access to CSC’s national computing infrastructure
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computing, or hardware reliability. Experience with GPU, FPGA, embedded, or specialized AI accelerator platforms. Experience with scientific programming, benchmarking, or reproducible experimentation
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Universitat Politècnica de Catalunya (UPC)- BarcelonaTECH | Barcelona, Cataluna | Spain | 14 days ago
conferences and journals on machine learning and networks, release the code in open access and actively participate in the international interpretability community. Where to apply Website https
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, and audio research, including Aalto University’s large-scale scientific computing cluster with CPU and GPU nodes, access to CSC’s national computing infrastructure including LUMI, and the Aalto
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/graduate staff. Where to apply Website https://jobs.energy.imdea.org/en/offer/429 Requirements Research Field Other Education Level PhD or equivalent Skills/Qualifications PhD in Artificial Intelligence
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Parallel numerical algorithms GPU computing Strong programming skills are very important. Experience with C/C++, Python, Julia, MATLAB, CUDA, or a comparable scientific-computing environment is desirable
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with high-performance computing, GPU programming, parallel programming, cloud computing, and/or related methods including running numerical simulations of complex workflows. Demonstrated technical