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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 14 days ago
their structural, release and stability properties. In parallel, strategies for embedding the microparticulate systems into inert hydrogel matrices will be developed, enabling their localization and retention
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full aircraft engine, running on the UK’s supercomputing services. There will be both engineering aspects to the project (around model validity) and computer science aspects (around parallel efficiency
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: Essential criteria A doctorate (or will shortly satisfy the requirements of a PhD). The doctorate must be in a relevant discipline area, such as statistical machine learning, computational and quantitative
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engineering aspects to the project (around model validity) and computer science aspects (around parallel efficiency and computational time). You will be working closely with engineers at Rolls-Royce and with
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these codes in C++ or Fortran Adopting these codes for multiple-CPU and/or GPU platforms via parallelization schemes. Validating these codes via canonical and real-world examples. Job Requirements: PhD in
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should have or be close to completing a PhD in aerospace engineering (or equivalent qualification and experience), with experience in fixed/rotary wing air vehicles. What you need: Strong understanding
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for large samples at ESRF ID16A using multislice tomography approaches. You will lead the development of and work with parallelized computer models to simulate how coherent waves travel through materials with
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PhD) EUR 3,000 Starting package from EUR 10,000 to EUR 20,000 per year Applicants will be encouraged to apply for complementary external funding (e.g., MSCA or EMBO fellowships) in parallel to/following
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of capabilities such as AI training and inference at scale, and tight AI-simulation coupling. What is Required: PhD in Physics, Chemistry, Computational Science, Data Science, Computer Science, Applied Mathematics
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awarded to students who are enrolled in non-award courses, or up to four years, in the cases of students enrolled in a PhD. Scientific advisor: João Tiago Paulo Workplace: INESC TEC, Braga, Portugal