Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- University of Bergen
- NTNU - Norwegian University of Science and Technology
- NTNU Norwegian University of Science and Technology
- University of Oslo
- UiT The Arctic University of Norway
- BI Norwegian Business School
- Norwegian University of Life Sciences (NMBU)
- NHH Norwegian School of Economics
- Simula UiB AS
- University of Agder
- University of Agder (UiA)
- 1 more »
- « less
-
Field
-
(D): To work with algorithms for wearable data University of Manchester (UK): To learn mathematical modelling of hormone rhythms. University of Bristol (UK): To learn mathematical modelling of hormone
-
. The primary objective of SURE-AI is to create a new generation of algorithms for inference and decision-making by pushing the boundaries of computational techniques. The research emphasizes efficiency in
-
with algorithms for wearable data University of Manchester (UK): To learn mathematical modelling of hormone rhythms. University of Bristol (UK): To learn mathematical modelling of hormone rhythm
-
endocrinology. Research Fields: Endocrinology, Chronobiology, Reproduction, Digital Health, Medical Sensors, Systems Physiology, Internal Medicine Secondments: University of Ulm (D): To work with algorithms
-
-resolution wearable sensor streams, and endocrine test outcomes. Intelligent Artifact Detection: Develop cutting-edge Machine Learning algorithms to automatically identify, flag, and mitigate data artifacts
-
to seamlessly integrate complex hormonal data, high-resolution wearable sensor streams, and endocrine test outcomes. Intelligent Artifact Detection: Develop cutting-edge Machine Learning algorithms
-
of novel satellite data analysis algorithms and solutions that will form the technology foundation for new products. The position is for a period of three years. Admission to the PhD programme is a
-
) on physical robots. • Use evolutionary algorithms to optimize both the robot’s body and brain together. • Apply quality-diversity methods to discover a wide range of high-performing designs
-
the fundamental limits of quantum error correction (QEC) while concurrently advancing efficient decoding algorithms for quantum error-correcting codes in the near-term, noisy intermediate-scale quantum (NISQ) era
-
algorithms for inference and decision-making by pushing the boundaries of computational techniques. The research emphasizes efficiency in resource and data usage, reducing environmental impact, and ensuring