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National Institute of Research and Development for Electrochemistry and Condensed Matter | Romania | 1 day ago
of materials. • Numerical simulation (CAE) of fluid dynamic behavior using finite element analysis (FEM) and strength criteria. • CAD design (Catia V5, Ansys). Important skills include openness to learning and
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the pulsed electric field so that all microalgae in the solution receive the electric field for equal durations. The aim is to continue the numerical study (CFD) already undertaken in this field to find
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-body contributions. Tasks: Independent scientific collaboration on the above-mentioned project Data analysis and interpretation, numerical modeling, and preparation of scientific publications
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advanced professional level work of considerable difficulty, requiring the analysis and interpretation of fiscal data, and the application of accounting theory and principles to various aspects
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biologists in study design, development of bioinformatic pipelines and analysis modules for the analysis and publication of high-throughput omic data from cancer studies including Phase I / II or III clinical
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group focus on the development and analysis of continuous and discrete models in connection with convex and nonconvex optimization problems and monotone inclusion systems. Our ideal candidate already has
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report of the courses attended on the following topics: Analysis of Partial Differential Equations, Continuum Mechanics and Fluid Dynamics, Functional Analysis, Numerical Analysis, Probability and
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interactions. Development and use of numerical simulation tools to study plasma–dark matter interactions. Analysis of astrophysical data to search for observational signatures of this physics. The group also
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interface. - Deployment, compilation, and execution of the ECCO-Darwin model on the supercomputer - Numerical developments on the ECCO-Darwin model code - Analysis of numerical model outputs - Processing and
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developments in sensor design, dataset transmission, data analysis, and numerical modeling to distinguish between normal and abnormal features. Here, the goal is to develop machine learning algorithms