Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Employer
- Oak Ridge National Laboratory
- Duke University
- UiT The Arctic University of Norway
- University of Glasgow
- University of Texas at Austin
- AI4I
- CNRS
- Centre Euopéen de Recherche et de Formation Avancée en Calcul Scientifique (CERFACS)
- Eindhoven University of Technology (TU/e)
- Forschungszentrum Jülich
- MOHAMMED VI POLYTECHNIC UNIVERSITY
- Nature Careers
- Universitaet Muenster
- University of Arkansas
- University of California Riverside
- 5 more »
- « less
-
Field
-
for a duration of six years. NumPEx contributes to the design and the development of numerical methods, software components and tools that support future productive European exascale and post-exascale
-
computational imaging. The project aims to develop a novel optical phase and refractive-index tomography platform and computational algorithms capable of overcoming the challenges of multiple scattering in thick
-
reconstruction methods (e.g., Born/Rytov approximations, multislice or multiple-scattering models). Proven experience in scientific programming and numerical computing (MATLAB, Python, or C/C++), including
-
regulations related to health care Attention to detail and accuracy Computer literacy Preferred Qualifications Experience and demonstrated skill with using the teaching method of asking questions for self
-
experience Demonstrated programming expertise in MATLAB and/or Python (object-oriented design, numerical methods, scientific visualization) Prior experience in scientific computing or within the subsurface
-
) and Computational Fluid Dynamics (CFD), for polymer composite manufacturing processes Perform multi-physics simulations involving coupled thermal, mechanical, and material behavior across multiple
-
for representative substrates. As running multiple experiments in parallel during each optimization step will greatly reduce the evaluation time and experimental effort, a batch selection strategy will be implemented
-
methods will be given by the supervisory team. Work towards achieving the Objectives will run in parallel through the project, broadly along the following timeline: Year 1: literature review, desk-based
-
developed to test rates of bioactivity under a range of environmental conditions. Methods A range of techniques will be used to investigate the multidisciplinary project aims. For example: Sample collection
-
algorithms in the context of sparse tensor operations and apply them to real-world datasets. Parallel Computing: Explore opportunities for parallelism in the tensor completion process to enhance computational