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of a call for awarding a research fellowship (RF) in the scope of the research project AQUALEARN – Machine learning-based digital twins for real time anomaly detection in water supply systems. 3
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fellowship: Novel microfluidics and machine learning tools for unravelling environmental microbiomes Within the remit of the ERA Chair project REACTORS 5.0 “Sustainable REACTOR and microreactor designS
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: Alexandre José Malheiro Bernardino (ist13761) Organic Unit: Scientific Area of Systems, Decision and Control Scholarship Theme: Computational Auditory System Simulators and Machine Learning-based Optimisation
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; - academic curriculum with background on the computer science and machine learning background; - previous research and professional experience on the scientific domains of the work. Additional Information
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | 4 days ago
). Experience in machine learning methods, including data preprocessing, model selection, and performance evaluation. Familiarity with programming languages commonly used in these domains (e.g., Python, MATLAB
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to the stage of contracting the scholarship, and before that, they may be replaced by a declaration of honor. Preferential factors: • Expertise in Machine Learning; • Experience in developing machine learning
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Engineering, or related fields. They must have proven experience in the development and programming of Information Systems; prior experience in applications based on Data Analytics/Machine Learning and data
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programming, and/or human-computer interaction (UX), and/or application of Machine Learning. Sense of responsibility and ability to communicate and integrate into multidisciplinary work teams. 3. Financial
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experience – 40% Evaluation of academic performance and/or relevant professional experience in machine learning, AI, software engineering, or security-related domains. Research track record and scientific
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: familiarization with the workflow platform and machine learning concepts; development of web interfaces for data silo registration and federated training sessions monitoring; implementation of back-end components