Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
that includes material space construction and exploration, candidate selection and verification, providing data for machine learning models to optimise membrane properties, structure, and fabrication. The fellow
-
mechanistic process models with machine learning for accuracy, generalization, and interpretability. Uncertainty-aware AI: robust inference under noise, drift, and changing conditions; knowing when a model is
-
Assessment of Cardiac Function and Outcome Prediction using Artificial Intelligence and Echocardiography". The project aims to develop novel AI models based on self-supervised learning and multimodal machine
-
machine-learning methods to enhance predictive capability and enable adaptive process control. Experimental work will include laboratory- and industrial-scale forming trials, supported by comprehensive
-
(as machine learning techniques, etc.). Personal characteristics In the evaluation of which candidate is best qualified for the PhD position, emphasis will be placed on education, experience and
-
(ph.d.) in artistic development work at the Norwegian University of Science and Technology (NTNU) for general criteria for the position. Preferred selection criteria Experience with machine learning
-
, epidemiology, high dimensional statistics, infectious disease, machine learning and mathematical modelling. The centre has numerous collaborations with leading biomedical research groups internationally and in
-
broad range of areas, including causal inference and time-to-event analysis, clinical trials, epidemiology, high dimensional statistics, infectious disease, machine learning and mathematical modelling
-
machine learning applied to geophysical signals. Experience in managing research projects. We encourage early career (post PhD), mid-career and senior researchers to apply. LanguagesENGLISHLevelGood
-
outcomes and economic performance, specifically addressing challenges such as overdiagnosis in cancer care. We will utilize economic theory, simulation, economic evaluation and machine learning to quantify