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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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. -------------------------------------------- Contribution to the adaptation, evolution, and integration of mission planning simulator services for drones, counter-drone measurement sensors, and critical infrastructure simulation. Collaboration in
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simulation : Aspen HYSYS/Plus. • Optimization skills: experience with GAMS or pyomo (or similar), including model formulation. • Life Cycle Assessment (LCA): experience with, e.g., Brightway2/SimaPro/Activity
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health research on Virus evolution using Organoids models (APROVO)” in the frame of the APROVO Project (Proyectos de Generación de Conocimiento, Ministerio de Ciencia, Innovación y Universidades). The PhD
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performance of molecular dynamics studies on molecular diffusion models in membranes. The research is oriented towards the study of the physicochemical behavior of new systems based on paramagnetic ions with
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of work: low-resolution algorithms, model optimisation with HPC techniques, edge computing, quantum computing, energy-efficient compact data structures, NLP optimisation. Justification of duration A
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computing for sustainable development, algorithms for energy efficiency, or AI for modelling social behaviour in relation to sustainability. Justification of duration A contract duration of three months is
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CONTRACTS FOR THE TRAINING OF DOCTORAL STUDENTS FUNDED BY THE UPV'S RESEARCH STRUCTURES – SUBPROGRAMME 2 (PAID-01-22) 109772 Research on understanding and optimization techniques for transformer models, with
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and validating architectures tolerant to faults and interference (jamming/spoofing) and robust to radiation-induced degradation, adaptive beamforming, and AI-based radio control. The role spans models
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for Bioengineering of Catalonia (IBEC) is looking for a Pre-doctoral Researcher to conduct her/his predoctoral training on advanced cancer in vitro models to study critical steps of the cancer immunity cycle. The aim