38 genetic-algorithm-computer-"Washington-University-in-St" positions at Linköping University in Sweden
Sort by
Refine Your Search
-
application! Work assignments As a postdoctoral fellow, your main task will be to conduct cutting edge computational social science research. The research will be carried out within the context of the Swedish
-
application! Work assignments As a postdoctoral fellow, your main task will be to conduct cutting edge computational social science research. The research will be carried out within the context of the Swedish
-
qualifications required for employment as associate professor. The Computer Vision Laboratory (CVL) is looking for an assistant professor in machine learning with a focus on computational photography. CVL is a
-
application! We are looking for a PhD student in Wireless Communication and Computer Vision. Your work assignments Point clouds (PCs) are sets of three-dimensional (3D) data points and their attributes
-
application! We are seeking up to two advanced-level students in computer science, computer engineering or closely related area as research project assistants (programming, system administration). The position
-
of scientific data, e.g. from image acquisition modalities or scientific simulations. Efficient algorithms are at the core of most of these data analysis and visualization applications. The focus of this Ph.D
-
with machine learning and generative AI algorithms, with working knowledge of deep learning frameworks such as PyTorch or TensorFlow is considered a strong advantage. • Extensive experience in multi
-
CST Microwave Studio, HFSS or EM Pro for antenna modeling and design is required, as is experience with programming languages like MATLAB, Python, or similar for antenna array analysis and algorithm
-
like computational complexity of algorithms. It’s also fairly common that we need to drill down into the code for some tool to figure out what’s wrong, so being able to read and understand code is
-
application! Work assignments Subject area: Computational studies of the influence of microstructural features on the structural integrity of metallic materials using machine learning Subject area description