Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
. TASKS: Mathematical modeling and development of inverse methods (e.g. Bayesian inversion, optimization based methods, sparsity promoting methods based on L1-norm minimization and compressed sensing
-
factorizations, least-squares problems, descriptive statistics, probability rules, probability distributions, statistical significance, hypothesis testing, estimation, Bayesian paradigm. Benefits:https
-
Bayesian neural networks. Excellent analytical, technical, and problem-solving skills Excellent programming skills in Python and PyTorch including fundamental software engineering principles and machine
-
candidate will show in-depth methodological and applied knowledge in the field of machine learning, especially deep learning, experiences in the area of uncertainty quantification, generative and Bayesian