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about LIST? Check our website: https://www.list.lu/ How will you contribute? You will model the mechanical properties and plastic deformation of materials with diverse compositions of Ti and C and
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Materials, Bioinspired Materials and Sustainable Materials. For more details, please view https://www.ntu.edu.sg/mse/research . The Decarbonisation Programme “Singapore Max-Planck Alliance for the Sustainable
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INESC TEC is accepting applications to award 4 Scientific Research Grant - NEXUS - CTM (AE2025-0564)
programme Reference Number AE2025-0564 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2025-0564
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container platform on Google Cloud. Our technology stack is Python, Django, React, Typescript, GitLab, Terraform, and Google Cloud. We use boilerplate solutions and turnkey templates to scale efficiently
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Responsibilities include the following: Conducts research in the area of aging, balance, fall rehabilitation, app development, and biomechanics. Assists with data post-processing. Assists in programming using Python
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technologies: Software Design Methodologies: Object Oriented Design and Analysis, Unified Modeling Language (UML), Agile/Scrum, Waterfall; Programming Languages: C/C++, C#, .NET, Java, Python; Scripting
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account of the history of geometric mechanics is given in these slides: https://klasmodin.github.io/assets/pdf/modin-geometric-mechanics-lund-2023.pdf More posts related to our research are available here
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E-mail victor.rfernandez@upm.es Requirements Research FieldComputer science » OtherEducation LevelBachelor Degree or equivalent Skills/Qualifications - Python (pandas, sklearn) - Pytorch
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postdoc will: ● Start by familiarizing with existing research and methods for genome interpretation, such as the AI4GI lab previous publications (https://academic.oup.com/nar/article/50/3/e16/6430850?login
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. Proficiency in Python, MATLAB, or R. Strong quantitative and analytic skills. Preferred Qualifications Experience with evidence-accumulation models (DDM, sequential sampling, Bayesian models). Experience with