Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
-
Field
-
description You will be contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will
-
-constrained machine-learning (ML) models in simulations of turbulent flows. You are expected to contribute to research and development in data-driven methodologies for turbulence modeling in LES (i.e., wall and
-
postdoctoral position. Applications are invited for a one year postdoctoral position in the field of Neuromorphic Spintronics at the Department ofElectrical and Computer Engieering, Aarhus University, Denmark
-
requirements, including link budgets, beam steering, and orbital pointing dynamics. • Experience with optimization methods and physics-informed machine learning. • A strong publication record in antennas
-
. These variables include cover crop growth, crop nitrogen, yield, and tillage practices. You will develop novel algorithms to integrate data-driven machine learning and process-based radiative transfer models
-
At the Technical Faculty of IT and Design of the Department of Sustainability and Planning, Copenhagen, a position as Postdoctoral researcher in Geospatial Machine Learning for Predicting Land Use
-
employ cutting-edge single-cell and spatial omics technologies with bioinformatics and machine learning to decipher principles of gene regulation underlying cell identity and its disruption in human
-
metabolism Strong problem-solving skills and the ability to develop novel computational methods for data integration and analysis Experience with machine learning approaches for biological data modeling and
-
, unlocking reliable perception and navigation where GNSS/GPS cannot be trusted or is unavailable. The project combines ultrasonic sensing, probabilistic perception, and machine learning with advanced robotics
-
at the intersection of AI, RF, and wireless communication. Your main tasks include developing machine-learning methods for wireless interference detection, mitigation, edge intelligence, and applying AI to optimize RF