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Field
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are looking for candidates who have experience with developing AI or machine learning models, as well as bacterial sequence analysis. You should be familiar with relevant programming languages such as Python
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to applicants with published research or exceptional academic performance. Experience in computer vision or audio processing is desirable and will be considered an advantage. A doctoral candidate is expected
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in crystalline rocks. Drilling optimization using machine learning, e.g. predicting rate of penetration (ROP) and wear. Investigate the possibilities in automation and robotization and the use
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consumers. You'll gain deep interdisciplinary experience—combining multiple data layers and approaches including bioinformatics, machine learning, food safety management, regulatory science, genomics and user
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/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning packages
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knowledge of wireless communications, and signal processing. You have at least intermediary knowledge of machine learning algorithms, including federated learning, split learning, and graph neural networks
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Failure Analysis of Composite Sleeves for Surface Permanent Magnet Electrical Machines This exciting opportunity is based within the Power Electronics, Machines and Control (PEMC) and Composites
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control subjects based on diffusion MRI images and functional MRI responses. Duties include: Developing machine-learning and/or deep learning pipelines for classifying patients of optic neuropathies and
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This exciting opportunity is based within the Power Electronics, Machines and Control (PEMC) and Composites Research Groups at the Faculty of Engineering, which conduct cutting-edge research
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interest in neuro-behavioral sciences and a passion for behavioral signals. Demonstrable experience in advanced data analysis and data collection. Familiarity with machine learning and proficiency in Python