Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
), (c) estimation methods for latent variable models (e.g., two-step approaches or approximate maximum likelihood estimation), or (d) meta-analytic models to address complex data structures (e.g., spatial
-
enables improved resilience as partitions of the grid can be independently powered. This PhD project aims to develop the methods needed to take advantage of this opportunity. This includes methods for pre
-
-based computed tomography, with numerical simulations informed by microstructural data. The successful candidate will work at the interface between experiments, modelling, and data-driven methods
-
tomography, with numerical simulations informed by microstructural data. The successful candidate will work at the interface between experiments, modelling, and data-driven methods. Particular emphasis will be
-
response behavior (such as rapid guessing, cheating, or careless responding), (c) estimation methods for latent variable models (e.g., two-step approaches or approximate maximum likelihood estimation), or (d
-
engineers in seamlessly combining quantum and classical methods for tackling complex problems? How to verify computing is quantum-safe by simulation of classical computing for data-intensive tasks while
-
cooperation with the Institute of Marine Research. The core of the position will be on development of new deep learning methods for segmentation/classification of data with limited and weak labels. Your may
-
., probability, analysis), eager to conduct cutting edge research in the field of uncertainty quantification, in particular the theory and methods known as predictive Bayes. Predictive Bayes theory involves
-
The position An exciting postdoctoral position in method development for spatio-temporal medical data is available in the UiT Machine Learning Group at the Department of Physics and Technology . Goal: Develop
-
response behavior (such as rapid guessing, cheating, or careless responding), (c) estimation methods for latent variable models (e.g., two-step approaches or approximate maximum likelihood estimation), or (d