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thermodynamic cycles by combining two complementary approaches: - Generative models derived from artificial intelligence, capable of proposing new process architectures; - Superstructure-based optimization
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computational approaches that integrate process-induced stresses into the structural design stage. Project goals The objective of this PhD project is to develop a topology optimization framework for LPBF
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reconstruction using Fourier domain optical normalization." Light-Science and Applications 5: el 60389, 2016. http://dx.doi.org/10.1038/Isa.2016.38 Henn MA, et al: "Optimizing the nanoscale quantitative optical
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and Drug Delivery Systems for Enhanced Bone Regeneration” (Reference: PROID2025010017). This project focuses on the optimization of additive manufacturing processes (MEX) and scaffold performance
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been performed in a fragmented manner, within other Surgical Units. The establishment of a Plastic Surgery Unit will require a significant organizational effort to implement and optimize care pathways
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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | 6 days ago
. These simulations are run on highly parallel supercomputers on which both the hardware and the software are optimized for the task at hand. While the computing power of each processing unit is still increasing, the
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improve scalable processes to manage large budgets efficiently and reduce manual effort. The full job description is available, here: https://openlearning.mit.edu/jobs Job Requirements REQUIRED: Bachelor’s
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19 Mar 2026 Job Information Organisation/Company UNIVERSIDAD DE LAS PALMAS DE GRAN CANARIA Research Field Engineering » Biomedical engineering Engineering » Computer engineering Researcher Profile
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homogeneous impregnation [3]. The objective of this PhD is to optimize the impregnation of hemp wrapped yarns intended for composite applications by controlling all transformation processes from the fiber
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distributed data processing closer to IoT devices. However, optimizing service placement in Fog environments remains a challenge due to the variability of Fog node resources, latency and energy constraints, and