Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
learning in simulated and indoor/outdoor environment. Reasonable results can be achieved in high signal-to-noise ratio environments; further research is required to improve deep learning in fast variation
-
itself and changes the way it should appear at high photon energies. The details of this process can be explored both analytically and numerically, the latter using simulations of magnetohydrodynamics (MHD
-
offshore wind farms are coming online with tighter fatigue designs and more aggressive control strategies, your research will seek to assist decision-making (e.g. during operation, but also during design) to
-
in Trondheim. At NTNU, 9,000 employees and 43,000 students work to create knowledge for a better world. You will find more information about working at NTNU and the application process here. ... (Video
-
Supervisory Team: Prof Neil Sandham PhD Supervisor: Neil Sandham Project description: This project is focused on scale-resolving simulations (large-eddy and direct numerical simulation) combined
-
Administration, Entrepreneurship section, at Umeå School of Business, Economics and Statistics with Prof. Norbert Steigenberger as your main supervisor. With this PhD project, funded by Lundbergs Foundation, we
-
simulation for detector support mechanics and cooling, as well as an in-house facility to design, develop and build silicon detectors. At Purdue we also operate a Tier-2 computer center, providing resources
-
, including detector operations, upgrade, software, and physics analysis. The group is deeply involved in detector upgrade projects using a center of excellence for composite manufacturing and simulation
-
Nancy and the long-standing experience in sophisticated computer simulation studies from Leipzig, promising unique prospects in advanced education of PhD students via research into this important field
-
Applications are invited for a position in the rapidly expanding data analytics run by Prof Adam Dubis. The main focus of the team is to develop deep learning tools for prediction of disease progression