Sort by
Refine Your Search
-
computer vision. The dominant approach is based on deep neural networks applied to RGB images. These models have disadvantages such as: a) the need of large quantities of annotated data, which requires
-
learning. Experience with deep learning algorithms for object segmentation/recognition is also welcome. Proficiency in C++ and Python. Proven track record of high-impact publications in related fields
-
experiments and numerical simulations and will be divided into three parts: Microstructure: 1.1. Experimental Characterization: Using X-ray tomography, image analysis with conventional tools or deep learning
-
particular their detection using at least one of the above methods. - Languages and coding: python (essential), good background in Computer Sciences (expertise in AI/deep learning welcome). Values: enthusiasm
-
, Python, Bash). Good level on machine learning. Good level of written and oral English. Ease in a multidisciplinary environment, taste for teamwork, interpersonal skills. Scientific curiosity