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for detection and/or classification of bioacoustic signals. Extensive experience with programming (Matlab, R, Python) including GPU programming is required, and familiarity with edge-based machine
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HPC resources (NAISS) and local GPU infrastructure. This Postdoc position is part of the eSSENCE graduate school in data-intensive science. The school addresses the challenge of data-intensive science
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Center) centralized HPC services, including both CPU and GPU cutting-edge technologies. Under the direction of the HPC team leadership, maintain, configure, and provide automation support for high
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matière d’efficacité énergétique - par rapport aux solutions actuelles du secteur basées sur des GPU ou des NPU. Plus précisément, il vise la conception de puces dédiées à l’accélération de fonctions
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. Deep expertise in Linux and HPC architecture, including heterogeneous CPU/GPU compute, workload scheduling, high-speed interconnects, parallel or distributed file systems, cluster management, artificial
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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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. Experience or training and deploying models on Graphics Processing Unit ( GPU ) hardware. Working Conditions Needs to be able to successfully perform all required duties. Office/research environment
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demonstrate examples of your independence in research. It is also appreciated if you also have some pedagogical experience. Knowledge of and skills in MPI and GPU programming, along with experience
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un premier temps de brancher dans Coddex une analyse in situ avec l’interface de programmation d’application (API) Catalyst (https://catalyst-in-situ.readthedocs.io/). Il sera alors possible
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clinical datasets, high-end GPU and storage infrastructure, international research collaborations, and dedicated funding for international conference participation. Supervision The PhD candidate will be