Sort by
Refine Your Search
-
physics or computer science, with a solid background in AI/machine learning techniques. A background in plasma transport phenomena as well as an experience with data analysis, statistical methods, and
-
or oceanography. Research background should demonstrate competence -- or at least a clear and strong interest -- in artificial intelligence and machine learning to be applied in the field of environmental sciences
-
. Fujii, K. & Nakajima, K. Harnessing disordered-ensemble quantum dynamics for machine learning. Phys Rev Appl 8, 024030 (2017). 2. Rudolph, M. S. et al, Generation of High-Resolution Handwritten Digits
-
or as materials for transportation. Intensive calculations within the framework of density functional theory (DFT) will provide the basis for building machine-learning models to explore the range
-
the relationships between manufacturing parameters and battery cell performance. The collected data and the unraveled insights will be used to calibrate and validate pioneering physical and machine learning models