Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- NTNU - Norwegian University of Science and Technology
- NTNU Norwegian University of Science and Technology
- University of Oslo
- University of Bergen
- University of South-Eastern Norway
- jobs.ac.uk
- Nord University
- Norwegian Institute of Bioeconomy Research
- Norwegian University of Life Sciences (NMBU)
- BI Norwegian Business School
- Molde University College
- NTNU
- Oslo Metropolitan University
- UNIS
- UiT The Arctic University of Norway
- University of Inland Norway
- University of Stavanger
- 7 more »
- « less
-
Field
-
be the head of the computing unit. About the project The primary research goal will be to create quantitative performance models that describe a range of numerical methods, parallel programming models
-
the computing unit. About the project The primary research goal will be to create quantitative performance models that describe a range of numerical methods, parallel programming models, and hardware platforms
-
interpretable framework for probabilistic unsupervised learning for structured biological data. The successful candidate will: Develop probabilistic factor models and scalable inference algorithms for structured
-
learning models for segmenting and interpreting forest point clouds and rebuild them as real-time, incremental estimation systems. The work supports navigation, self-localization, and traversability work
-
leader is Associate Professor Soledad Gonzalo Cogno. About the project The successful candidate will contribute to the development of mathematical and computational models to enquire about the mechanisms
-
renewable energy use, energy security, and the reliable operation of hydro-dominated power systems. The project will focus on how AI can support advanced optimization models for hydropower and energy-system
-
the mentorship of Professor Emre Yaksi. This project aims to unravel how brain architecture shapes sensory processing in the zebrafish forebrain. Using zebrafish as a powerful vertebrate model organism — owing
-
of neural networks, for reconstructing MR images directly from MR signals. By incorporating a physical model of the MR signal into the training of the INR network, we aim to compensate for the effects
-
of Marine Technology at NTNU has a vacancy for a PhD Candidate in Deep Learning enhanced FSI modelling of Multi-modular Floating Structures. The position is part of the AIMOS project (Artificial Intelligence
-
to investigate the potential of using Implicit Neural Representation (INR), a class of neural networks, for reconstructing MR images directly from MR signals. By incorporating a physical model of the