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Surrey’s track record of translating fundamental machine learning, spatial audio and audio-visual AI into groundbreaking creative technology. About you We seek a talented Research Fellow to investigate
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reliability. Prospective applicants for this PhD proposal should have the following qualifications: M.Sc. degree in communications engineering, mathematical engineering, electrical engineering, computer
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familiar with data science and machine/deep learning toolkits. Experience with model deployment and the usage of MLOps tools (Dockerization, CI/CD pipelines, edge infrastructure, etc.) is a plus. As a PhD
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the reference number 27697, via our online portal: Apply now via https://jobs.uksh.de/job/Kiel-PhD-%28mfd%29-Statistical-Genetics-Machine-Learning-Schl-24105/1279933701/ For more information visit: www.uksh.de
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time off. To access this tool and learn more about the total value of your benefits, please click on the following link: https://resources.uta.edu/hr/services/records/compensation-tools.php CBC
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/postdoc-ub4h-digital-technologi… Requirements Specific Requirements A PhD in educational sciences, engineering education, learning sciences, or a related discipline. Knowledge of hydrogen technology or
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The research program involves the study of machine learning
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federated learning, AI security and privacy, quantum machine learning (QML), robotics, and/or AI-driven discovery in science and engineering (e.g., genomics, bioinformatics, drug discovery, infectious disease
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(SHORES) and the Division of Engineering, New York University Abu Dhabi, seek to recruit a Postdoctoral Associate to work on a fascinating project focused on the development machine-learning powered digital
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for further studies in the field of scientific computing involving machine learning models for viscoelastic fluid flows. Legislation and regulations: Law Nº. 40/2004, of 18th August, in its current wording