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obligatory requirements: Advanced knowledge of 3D modeling and experience in areas relevant to the project. Availability is valued The proof of enrolment must be made until the contract signing date, and the
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for Research Grants of the Foundation for Science and Technology, I.P. (model below, for student enrolled in a non-academic degree course integrated in the educational project of a higher education institution
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also present the following obligatory requirements: Advanced knowledge of 3D modeling and experience in areas relevant to the project. Availability is valued. The proof of enrolment must be made until
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assigned and model safe, professional art-handling practices. Exhibition assistance: works collaboratively with theVisual Arts Cutrator, student interns, guest curators, visiting artists, and facilities
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Intelligence at The University of Queensland, this newly established lab is on a mission to empower expert decision-makers by harnessing the power of AI to tackle complex challenges. With a strong emphasis on
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modeller to help lead a collaborative research programme between the University of Queensland and King Abdulla University of Science and Technology (KAUST) with Prof David Suggett. Our shared goal is to
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Transport? Based in the Institute for Transport Studies at the University of Leeds, you will primarily contribute to the modelling and simulation of the integrated optimisation of Vehicle-to-Grid (V2G) energy
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for developing the microscopic models for magnon excitations for various experimental systems Numerical and analytic studies of the magnon thermal Hall effect for experimental detection. Requirements A PhD degree
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www.euraxess.pt , and on the Polytechnic Institute of Beja website www.ipbeja.pt . The document models identified in Article 6(1)(d) of Law 40/2004 of August 18 (Research Fellow Statute) can be consulted in
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Koziarski Lab - The Hospital for Sick Children | Central Toronto Roselawn, Ontario | Canada | 3 days ago
program at The Hospital for Sick Children, University of Toronto, and the Vector Institute. Our research group focuses on developing machine learning-based pipelines that leverage generative models and