Sort by
Refine Your Search
-
computational engineering, mathematics, computer science, physics, engineering or a related field Strong background in numerical methods and machine learning Proficiency in at least one programming language
-
results and to make parameter estimation more efficient. The project will apply and evaluate these new methods at different sites and time periods, compare them with established approaches, and finally
-
related field Strong background in numerical methods and machine learning Proficiency in at least one programming language (Python, Julia, C++, …) Good analytical skills Good organizational skills and
-
Tensorflow or Pytorch is advantageous Experience in numerical methods for partial differential equations is beneficial Effective communication skills and an interest in contributing to a highly international
-
: Investigation of precipitation and crystallization processes in phosphorus recovery using experimental and numerical methods Supervisor: Prof. Sergiy Antonyuk C2: Experimental investigation and modeling
-
and ability to work both independently and collaboratively Experience with deep learning frameworks, such as Tensorflow or Pytorch is advantageous Experience in numerical methods for partial
-
these new methods at different sites and time periods, compare them with established approaches, and finally demonstrate their potential in a Europe-wide ecosystem reanalysis. The outcomes will include open
-
method implemented into the EURAD-IM. In atmospheric chemistry modeling, the 4D-var method is a powerful tool to assess the state of the atmosphere and the corresponding emissions that are in compliance