Sort by
Refine Your Search
-
simulation models and enriched by operational equipment performance data. To this end, physics informed machine learning techniques will be used to bring model data and real data together in a Digital Twin
-
We are seeking for a highly-skilled and self-motivated candidate with a strong mathematical background to do a Ph.D. on the fundamental aspects of graph machine learning with applications
-
will explore the use of cutting-edge scientific machine learning framework that blends deep learning with physics-based techniques to achieve the goals of (i) identifying precursors and mechanisms
-
Challenge: Analyse properties of biological systems Change: Develop novel control theory and machine learning methods to study natural systems and their robustness Impact: Produce new intelligent
-
Challenge: Generating realistic bathymetric maps at a large scale using satellite images and advanced machine learning methods. Change: Incorporating physics into satellite-derived bathymetry
-
Are you passionate about exploring the crossroads of machine learning, atmospheric science, and laser satellite communications? If so, we invite you to apply for this exciting research position
-
. Machine learning and artificial intelligence, currently revolutionizing the fluid dynamics field, can be powerful tools in such cases. However, they remain limited to simple scenarios involving single-phase
-
developers of JetBrains. More information is available here: https://lp.jetbrains.com/research/ai-for-se/. We are looking for a candidate who has: A Master’s degree in computer science, machine learning
-
learning beyond your comfort zone. Beyond your electrical engineering / computer architecture background, you have a keen interest to expand your expertise in the areas of machine learning and neuroscience
-
shall focus on state-of-the-art machine learning techniques, that can find patterns within vast amounts of data, to refine the estimation of flight trajectories and fuel consumption. Additionally, you