Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
or burn-resistant testing demonstrated experience with conducting microstructural characterization techniques such as SEM, TEM, XRD, EDS, EBSD, FIB/SEM etc., as well as physico-mechanical characterization
-
thermal stresses. Moreover, being able to correlate these properties with each other and link them to the microstructure of the fibers is an essential element for the development of new materials. Objective
-
microstructures along the entire process chain using machine‑learning (ML) techniques and validate soft‑sensor outputs against laboratory reference measurements Perform systematic laboratory flotation experiments
-
‘healing’ the thermoplastic matrix. The challenge of reuse is that blade materials vary based on several factors including microstructure, macrostructure, and loading history. This project directly aligns
-
to seek mechanistic insight into the electrode polarization processes as well as strategies for improving performance by optimization of composition, microstructure, and the interface to the proton
-
, public authorities in their decisions and businesses in their strategies. Do you want to know more about LIST? Check our website: https://www.list.lu/ How will you contribute? You will develop a multi
-
. Specific study objectives will concern: - development of open source codes based on FEM approaches - development of contact theories in finite elasticity for microstructured and electro-active biological
-
French National Research Institute for Agriculture, Food, and the Environment (INRAE) | Grenoble, Rhone Alpes | France | about 1 month ago
systems, both in the laboratory and in the field, to elucidate multi-physical and multi-scale couplings from the microstructure to the slope scale. Your work will enrich the modelling of instability and
-
demand systematic experimental studies that will investigate build characteristics such as microstructures, precipitates, etc., besides functional properties such as static as well as dynamic loading
-
electrification strategy, the research aims to develop a multidisciplinary framework that combines microstructure modeling, machine learning, and probabilistic simulation to link manufacturing parameters, foam