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solutions and applying them in real-world scenarios. Proficiency with machine learning frameworks and pipelines in SKLearn, Numpy, Pandas, and PyTorch. Proficiency with deep learning frameworks such as
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, and research team to ensure timely achievement of project deliverables. Undertake the following specific responsibilities in the project: i. Develop, train, and optimise deep learning models for object
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of physics- informed machine learning and deep learning, with applications to inverse problems in scientific imaging and the modeling of complex physical systems. The overall goal is to integrate the knowledge
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composition, production and performance. Improve existing datasets and create new ones useful for deep learning models Where to apply Website https://apply.interfolio.com/178410 Requirements Research
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, and artificial intelligence. Visual understanding has made remarkable progress due to advances in deep learning technologies. Furthermore, technologies that combine videos/images with natural
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https://www.academictransfer.com/en/jobs/357205/2x-phd-positions-in-the-mathema… Requirements Specific Requirements You have, or will shortly, acquire a Master's degree in either Mathematics
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/or spatial genomics, computational biology, machine learning, bioinformatics, and systems neuroscience. Prior experience with deep learning applied to biological data is a plus. Practical experience
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researchers with ample experience in MEG/EEG data analysis, BCIs, signal processing, deep learning for brain imaging analysis, biomedical statistics, dynamical systems and research on motor control. The lab has
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: The work plan addresses the needs in current Research and Development (R&D) projects in INESC TEC to build energy-efficient software prototypes for training deep learning models on large-scale
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. Into the second year, the project moves toward methodology refinement and Machine Learning integration. The student will execute a more ambitious cycle with a complex alloy system and integrate machine learning