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Field
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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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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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Universidade Lusófona´s Research Center for Digital Human-Environment Interaction Lab | Portugal | 2 months ago
Python Machine Learning Libraries (PyTorch, Keras, etc.); statistical and machine Learning expertise and supervised and unsupervised methodologies; Valuable Bonus Skills include: experience with Unity3D
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CIIMAR - Interdisciplinary Center of Marine and Environmental Research - Uporto | Portugal | about 1 month ago
research in microbial genomics, in particular related to natural products biosynthesis and using metagenomics and genomics datasets. Experience in machine learning and the application of artificial
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manufacturing, health and transportion: Interperability of systems Data Management Big data analytics AI and Machine Learning Experience in the organization of international events such as workshops and
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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
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Predictive Maintenance: employing big data analytics to assess ballast degradation and particle morphology, supported by machine learning algorithms. Data-Driven Numerical modelling Simulations: leveraging
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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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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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that combine machine learning and classical methods. Work Plan: -State-of art revier and publication of a review paper -Development of classical approaches -Development of hybrid approaches -Journal publication