180 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "U.S" Master positions
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: Environment Engineering, or similar. Where to apply Website https://www.ipc.pt/bupc/concursos/form/concursos_bolseiros Requirements Research FieldEnvironmental science » OtherEducation LevelMaster Degree
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 2 months ago
, reference no. 2023.18249.ICDT, financed by national funds through FCT/MCTES (PIDDAC Workplan: Development of methodologies and machine learning algorithms for the detection of anomalous behaviors in flow rate
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stage. 3. Preferential Factors Proven experience with decision support systems based on knowledge bases and machine learning. Previous experience in machine learning applied to dynamic systems or orbital
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for the exceptions expressly set out in nos. 3 and 4 of Article 5 of the referred Statute. (https://www.fraunhofer.pt/content/dam/portugal/fhp/careers/grants/Regulamento_Bolsas_Fraunhofer_Portugal_Research_2021.pdf
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of computational thinking and didactic knowledge in mathematics among future teachers of the Primary School; Prepare and submit scientific articles. Where to apply Website https://www.ipc.pt/bupc/concursos/form
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | about 14 hours ago
employees and an annual budget of over € 5 billion, the Helmholtz Association is Germany's largest scientific organisation. Where to apply E-mail personal@hzdr.de Website https://www.hzdr.de/job2208e
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to monitoring cracking in concrete bridges and viaducts through computer vision The work is supported by BRISA and will use as case study the viaduct over the Rio de Anços on the A1. Duration: 6 months Maximum
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Sciences, in the frame of the R&D project Soil O-Live - The Soil Biodiversity and Functionality of Mediterranean Olive Groves: A Holistic Analysis of the Influence of Land Management on Olive Oil Quality and
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to provide the supporting documents by the grant contracting stage. 3. Preferential Factors Proven experience with decision support systems based on knowledge bases and machine learning. 4. Work Plan The work
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machine-learning methods for sample segmentation and classification. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: The fellow will join the INESC TEC team within the LIBScan project, carrying