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manufacturing and manufacturing process. Are you a postdoctoral researcher or a PhD candidate who is about to graduate and has a passion for metal additive manufacturing, machine vision, data acquisition
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/supporting statement, CV and the details of two referees as part of your online application. see the University pages on the application process at https://www.jobs.ox.ac.uk/application-process The closing
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are in compliance with the necessary trainings (both at the lab and at the institutional level). Minimum Education and Experience: A PhD degree in Computer Science, Electrical/Computer Engineering, or a
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software in support of Department of Energy (DOE) mission applications across a broad range of scientific domains, including materials, biology, physics, and nuclear science. The successful candidate will
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have a PhD in Civil Engineering, Engineering Mechanics, or Mechanical Engineering. Applicants are expected to demonstrate research experience in the fields of structural modeling and machine-learning
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Master's and PhD students. Candidates will be responsible for creating a collaborative work environment within and outside QGG that integrates novel innovative research programs towards the green transition
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The opportunity The University of Liverpool is a key partner in a £14 million initiative (https://tinyurl.com/yc5z768m) to develop a sustainable, next-generation manufacturing facility, using
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to the effective computation of the data and numerical simulation. Where to apply Website https://resurseumane.ase.ro/non-gaussian-self-similar-processes-enhancing-mathe… Requirements Research
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schools, doctoral supervision, and software outputs central to the Centre’s mission. About You You will have, or be close to completion of, a PhD/DPhil in Statistics, Machine Learning, Data Science, or a
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, graphs); experience with analysis and processing of large volumes of data; development of reproducible scientific software; proficiency in Python and libraries (Pandas/NumPy and PyTorch/TensorFlow/Scikit