197 machine-learning-"https:" "https:" "https:" "EMBL EBI European Bioinformatics Institute" Master positions
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here: https://www.cesam-la.pt/en/calls/research-grant-under-the-project-swift… Where to apply E-mail carlagama@ua.pt Requirements Research FieldEnvironmental scienceEducation LevelMaster Degree
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NanoSeira – Quantum dot-based SEIRA nanosensors for monitoring organic micropollutants in aquatic environments , funded by FCT. The complete notice of the call is available here: https://www.cesam-la.pt/en
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to the table of scholarships awarded directly by the FCT, I.P. in the country (https://www.fct.pt/apoios/bolsas/valores ). The period of payment of the scholarship is monthly and through bank deposit, check or
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the following conditions: 1. Scientific Area: Computer Engineering 2. P. (CETP/0003/2022", under the following conditions: 1. Scientific Area: Computer Engineering 2. Admission requirements: a) The candidate must
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 2 months ago
the replicator equation. The focus will be on understanding the principles and number of coexisting species, and the quality of their dynamics. The candidate(s) will also apply data fitting algorithms/machine
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degree in Electrical and Computer Engineering, Mechanical Engineering or related scientific fields; - Be enrolled in a Doctoral Program in Intelligent Systems Engineering, Electrical and Computer
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, according as defined by FCT, I.P. (https://www.fct.pt/apoios/bolsas/valores ). Selection process Selection methods: Eligible applications will be scored on a scale from 0 to 20 points, taking into account the
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Verilog description. Work Plan - Become familiar with the design flow in Workcraft - Become familiar with Signal Transition Graph (STG) design - Become familiar with specifying state machines in Verilog
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Freiberg, Sachsen | Germany | about 1 month ago
separation models to control flotation processes. Your tasks # Develop and implement soft‑sensor concepts for continuous monitoring of ore microstructures along the entire process chain using machine‑learning
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optimisation. State-of-the-art digital models and AI tools that incorporate machine learning could enable predictions of the dry fibre forming that are subsequently used as input into the RTM process model