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.pdf JOB ADVERTISEMENT Recruitment of 1 Doctorate in the field of Research and development of new algorithms for processing and classifying physiological signals in ambulatory systems INESC TEC
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requirements: Master’s degree in Physics. The candidate must have previous experience with remote sensing data, burned area mapping algorithms and handling large databases. He must also have solid mathematical
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 24 days ago
. The candidate(s) may also be required to apply data fitting algorithms/machine learning algorithms to link models to biological data from the literature. The project integrates elements from dynamical systems
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to the limit set out in the RBI-ISEP. 4. ACTIVITY OBJECT / WORK PLAN The work plan involves the following tasks: - Design and computational implementation of methods, algorithms, and applications
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of autonomous monitoring units, including image sensors, edge computing units, batteries, solar panels, and LoRa/LTE communication modules. • Implementation of anonymous visitor detection and counting algorithms
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of an observatory of behavioural finance algorithms; 4) investigate on how NLP can understand and respond to financial issues; 5) Financial education, analysis of the impact of external variables and study of market
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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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algorithm of the PotionDB system (https://github.com/AndreRijo/potionDB ); • Evaluate the proposed improvements in a geo-distributed context, using appropriate benchmarks; • Document the proposed improvements
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in LIBS systems.; • Develop algorithms for correction and compensation of galvanometric scanning, ensuring accurate spatial correspondence of LIBS data.; • Implement automated pipelines for LIBS data
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value candidates with interest and/or experience in the following areas: a) Understanding of machine learning techniques, with interest in exploring algorithms such as regression, decision trees, Random