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Field
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related fields; In a Course that do not confer an academic degree, in the area or area related to that requested in the tender. Preferential factors: Previous experience in the development of fiber
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or area related to that requested in the tender. Preferential factors: Prior experience in parametric analysis and simulation of building thermal performance, Life Cycle Assessment, prediction and
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grant that does not confer a degree for a cumulative period of 2 years, consecutive or interpolated; Preferential factors: Experience in Development of and signal conditioning for piezoresistive sensors
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areas*; 2. Technical Skills - Experience in processing 3D point clouds (LiDAR or photogrammetry); Knowledge of GIS, remote sensing, or spatial analysis; 3. Research Experience (Preferred) — Previous
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directly by FCT, I.P. in Portugal, and 1569,64 euros, depending on the profile and previous experience of the candidate in the project area. The payment will be made by bank transfer. Selection procedure
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on the profile and previous experience of the candidate in the project area. The payment will be made by bank transfer. Selection procedure: The curriculum of the candidates (60%) will be evaluated based
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Faculdade de Ciências Médicas|NOVA Medical School da Universidade NOVA de Lisboa. | Portugal | 3 months ago
The work will be carried out at the facilities of the Faculdade de Ciências Médicas | NOVA Medical School (FCM|NMS), Universidade NOVA de Lisboa (UNL), in the research group “Computational and experimental
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your community involvement, interest and experience in energy issues, and academic merit. We will also consider your performance in an interview.
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be considered, in order to improve search efficiency. The approach will be evaluated mainly in simulation, using different experimental scenarios, and the results will support the preparation of a
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Gorlitz, Sachsen | Germany | 3 months ago
or environmental systems # Experiences with research on quantum and hybrid quantum–classical algorithms for solving partial differential equations # Implementation, testing and benchmarking of computational methods