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challenges of learning from network traffic, (ii) train original AI models that are designed to operate precisely on such data, and (iii) demonstrate the viability in production of AI-driven solutions for, e.g
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, environmental, and resource economics. Ideal candidates are those wishing to acquire research experience for a subsequent Ph.D. in Economics. Due to the short term appointment, applicants must have a Spanish tax
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to support machine learning model development to accelerate materials discovery: Perform high-throughput DFT and molecular dynamics simulations to investigate the thermodynamic, structural, and electronic
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expertise in analysing complex quantitative and computational data and/or rich qualitative data. • Proficiency or skills to learn a statistical software (e.g., R, Stata, Python). • Interest in contributing
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. Gramaglia, P. Serrano, C. Mannweiler, “ATELIER: service tailored and limited-trust network analytics using cooperative learning”, IEEE Open Journal of the Communications Society S. Henri, G. García-Avilés, P
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workflows). Ability to work effectively in English within an international research environment. High learning agility and a structured approach to complex problem-solving. Assets (Desirable, but not
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computing and decentralized intelligence where a swarm of nodes learns graph dependencies by effectively integrating the structure of distributed systems into neural network architecture. This approach
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, or programming. The selected candidate will join the undergraduate teaching team and may teach introductory and advanced courses such as: Programming I (Python) Programming II (C or other low-level languages) Data
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This doctoral position is part of GRAIL (“Gamma Radiation from the Atmosphere for Investigation and Learning”), a prestigious Horizon Europe Marie Skłodowska-Curie Actions Doctoral Network (MSCA-DN): https
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for converged Wireless-opTical cOnfiguratioNs”. The research will cover three key pillars: Artificial-Intelligence (AI)-driven models in the access domain, focusing on CF technology to efficiently acquire Channel