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-transparent materials, and the utilisation of deep learning algorithms to accelerate computational solutions. Scientific Objectives Develop a self-contained finite volume solver for solidification of multiphase
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 5 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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Grundstufe (praedoc) Limited until: 30.04.2029 Reference no.: 5311 Where to apply Website https://iventajobdata.eu/bestmedia/img/2284472/1912258/cl/5cf77b097cc38f6987463… Requirements Specific Requirements
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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | 7 days ago
of algorithms aligned with the needs of IT4Innovations projects. Full time equivalent: 0,5 - 1,0 Type of job contract: fixed term employment (ideally 1 year, or as agreed) Expected start of employment: 1. 5. 2026
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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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region of Portugal, although other tasks may be considered according to the profile of the recruited researcher. The researcher will be responsible for implementing spatial analysis algorithms, developing
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scheduling algorithms to ensure operation continuity and reliable information exchange among batteryless sensors. Where to apply Website https://lavoraconnoi.unitn.it/research-assignments/dipartimento-disi
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25 Jan 2026 Job Information Organisation/Company CNRS Department Institut de Recherche en Informatique Fondamentale Research Field Computer science Mathematics » Algorithms Researcher Profile First
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Genomics at Harvard Medical School Several positions are available in the Park Lab (https://compbio.hms.harvard.edu/ ). The aim of the laboratory is to develop and apply innovative computational methods
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and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees