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: Design, implementation and testing of new methods and algorithms so that SIESTA can harness the compute power of the latest generation of (pre-)exascale architectures and tackle novel scientific challenges
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, CU/DU/RU split). - AI/ML algorithms and methods for joint compute and radio resource management at the 6G edge leveraging accelerators - Control- and data-plane separation, real-time scheduling, and
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techniques and neural network techniques to adjust high-resolution X-ray spectra and infer physical properties of the emitting plasma. · Developing algorithms that optimise the adjustment of high-resolution X
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this short-term project we shall use active learning to accelerate the training of deep learning algorithms for optimising 2D material van der Waals (vdW) structure discovery. The goal is to make model
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Postdoctoral researcher in marine ecosystems modelling for the Marine and Continental Waters Program
of machine learning and AI algorithms and methods. Knowledge of species distribution models. Catalan and Spanish are valued LanguagesENGLISHLevelGood Research FieldOtherYears of Research Experience1 - 4
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Learning algorithms to identify gene content profiles that may underpin relevant phenotypic traits in existing eukaryotic species and their ancestors, and to explore the role of horizontal gene transfer in
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models and reconstruction algorithms. Develop or adapt scripts (e.g. in MATLAB, Python) to facilitate data analysis workflows. Prepare scientific reports, publications and presentations to disseminate
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3 Oct 2025 Job Information Organisation/Company Universidad de Alicante Department Department of Mathematics Research Field Mathematics » Algorithms Researcher Profile First Stage Researcher (R1
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analysis, AI algorithm modeling, testing, and integration into functional systems within the project scope. Specifically, in activities related to behavior modeling from IoT device data, generative AI
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computationally efficient algorithms. They will work with machine learning, deep learning, and NLP tools. Funding This contract is part of the GAP project (PID2022-139308OA-I00), funded by MCIN/AEI/10.13039