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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 20 days ago
, financed by EU and national funds through FCT/MCTES (PIDDAC Workplan: Machine learning algorithms, in particular deep learning ones, suffer from the phenomena of catastrophic forgetting, which hampers
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. Expertise is required or highly desired in one or more of the following areas: algorithms, analytical derivation, data analysis, coding, or mathematical modeling. Strong programming skills are highly desired
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Now” button in this form https://www.it.pt/Positions/OtherResearchPosition/8322 E-mail submissions will not be considered. (The cover letter and the CV are mandatory documents in the online application
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Now” button in this form https://www.it.pt/Positions/OtherResearchPosition/XXXX E-mail submissions will not be considered. (The cover letter and the CV are mandatory documents in the online application
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 7 days ago
, and approximation algorithms. The successful candidate will be expected to deliver a course similar to the outline presented here: https://www.utsc.utoronto.ca/~bretscher/c63/lectures.html
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distributed wireless systems" which is conducted in collaboration between Linköping University (LiU) and Lund University (LU). Read more here: https://elliit.se/project/machine-learning-for-sensing-in
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Sklodowska-Curie Doctoral Network linking 21 academic, cultural, and industrial partners to develop advanced nondestructive evaluation and data-driven digital tools for paintings and 3D artworks (https
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integration, and system integration for next-generation wireless systems. We envision programmable and intelligent cellular networks that can be dynamically and algorithmically instrumented and optimized
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designing and implementing advanced control algorithms to coordinate multiple energy sources including battery energy storage systems (BESS), solar PV, and diesel generators, and dynamically assign grid
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: The design and analysis of computational methods that accelerate AI/ML when applied to large scientific data sets; Energy efficient physics-aware algorithms, capable of distributed learning on high performance