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on earth, electricity generation as well as systems for the production of solar fuels or energy storage will have to rely on new materials and material configurations able to provide an optimal
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department is looking for an energy research eager candidate to join the group. The candidate will be asked to perform the following tasks: To develop energy management software that will enable optimal
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seeking a senior postdoctoral researcher (R2 level) to take on a leading technical role in the development of advanced modelling, control and optimization tools for smart energy systems. The selected
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. This role involves creating high-performance optical designs, optimizing them for compact configurations, and integrating optical fibers to enhance system functionality. Primary Functions: Optical System
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and experienced scientist to join our lab as Responsible of Protocol Development in Genomics. This role is crucial for ensuring the implementation and optimization of protocols in our lab, hence
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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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Description Industrial PhD: Application of artificial intelligence and data analytics to the optimization of industrial processes Where to apply E-mail doctorats.industrials.recerca@gencat.cat Requirements
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curiosity are expected. Main Responsibilities: Participate in the synthesis and characterization of organic ligands and MOFs. Collaborate with senior researchers on the design and optimization of materials
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Institut de Recerca Biomèdica de Lleida, Fundació Dr. Pifarré (IRBLleida) | Spain | about 16 hours ago
systems. •Data analysis and exploitation: preparation of management indicators and optimization proposals. •Preparation of periodic reports of results and support in internal and external audit processes
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the training and optimization of AI/ML models for the physical layer of wireless communications. Generative AI models for wireless channel generation, e.g., generative adversarial networks or diffusion models