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Field
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(No experience, Basic Knowledge, Solid Experience) Technical and Domain Knowledge Industrial Processes & Systems Artificial Intelligence and Machine Learning Cyber-Physical Systems and Sensing Innovation and
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with machine learning. Evaluation of the final solution. V - Initial grant duration: 5 months V.I - Renewal Possibility: Possibily renewable VI - Funding and financial conditions of the grant VI.I
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concrete affected by internal expansion reactions. The main tasks to be accomplished are: • Acquire knowledge about the expansive phenomena and their modelling, considering the thermo-hygrometric
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possible renewals, an accumulated period of 3 (three) years in this type of scholarship, consecutive or interpolated. Proven knowledge in: Data Science (Python) Machine Learning (Python) Remote Sensing
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related to Computer Science, Machine Learning, Data Science, Information Management or other related areas; Have skills in the development and application of machine learning models in supervised and non
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experience in Data Science/Machine Learning projects or initiatives (professional projects, coursework, internships, personal projects or hackathons, etc.) Knowledge and experience with the use of tools
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(spoken and written), academic excellence, autonomy, curiosity, and attention to detail. Resumes demonstrating knowledge of programming in Python and/or Matlab; computer vision, image processing, learning
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in different programming languages applied in the field of biology; knowledge of machine learning, biostatistical analysis, database creation and implementation; proficiency in English (written and
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spanning design, modelling and simulation of photonic systems, sensor systems, signal processing and device manufacturing, development of machine learning algorithms, and design of optical communication
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Machine Learning model will be developed, capable of adjusting the electric assistance to optimise the balance between performance and consumption. Finally, the system will be validated with a real e-bike