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:………..………………………………………………………………………………………………………………………………………… Management, with particular focus on the intersection of: Machine Learning Causal Inference Applied Field Experimentation Scientific Areas: Management, Economics, Information Systems, Computer Science, Data
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simulation of photonic systems, sensor systems, signal processing and device manufacturing, development of machine learning algorithms, and design of optical communication networks or power consumption and
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that, they can be replaced by a declaration of honour. Preferential factors: • Expertise in machine learning, information retrieval, natural language processing. • Expertise in conversational models and systems
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26 Aug 2025 Job Information Organisation/Company INESC TEC Research Field Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Country Portugal Application Deadline 8
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of a Professor Adjunto [senior lecturer], who will be given a public service contract of unspecified duration, in the field of Computer Engineering – Web Applications Development – Cross-platform and
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 2 months ago
, with application to biomedical flows (e.g. microcirculation) it is now intended to develop an improved algorithm for advanced particle tracking using machine learning. The algorithm should be tested in
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the formula 0,40PQ + 0,40PV + 0,20AI. PQ corresponds to the quantitative evaluation of publications in ISI/SCOPUS journals: in advanced statistical models (e.g., Machine Learning), as well as in programming
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of consultations from texts based on a provided example • Organization of the collected data and its submission to the EquiVet.AI project scholarship holders in the field of Computer Engineering and affiliated with
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(IMI, IMT, IRS, Census) with descriptive methods and causal econometric techniques. It will use various approaches to identify vacant dwellings, including machine learning algorithms to visually detect
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(IMI, IMT, IRS, Census) with descriptive methods and causal econometric techniques. It will use various approaches to identify vacant dwellings, including machine learning algorithms to visually detect