Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- University of Oslo
- NTNU - Norwegian University of Science and Technology
- NTNU Norwegian University of Science and Technology
- UiT The Arctic University of Norway
- University of Bergen
- University of Agder
- University of South-Eastern Norway
- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
- NORCE Norwegian Research Centre
- OsloMet
- University of Stavanger
- Østfold University College
- 2 more »
- « less
-
Field
-
and Regulations for the degrees philosophiae doctor (ph.d.) and philosophiae doctor (ph.d.) in artistic development work at the Norwegian University of Science and Technology (NTNU) for general criteria
-
exports, and to facilitate the sustainable development of wind power. The Centre is led by SINTEF, with research partners NTNU (Norwegian University of Science and Technology), UiO (University of Oslo
-
, explore, and reflect on AI for, through, and in creative practices. MishMash researchers will investigate AI’s impact on creative processes, develop innovative CoCreative AI systems and educational
-
complex biological systems. Research Environment & Collaboration The successful candidate will work at the interface of machine learning and biostatistics, developing new theory, algorithms, and scalable
-
of Artificial Intelligence (AI), and therefore a fundamental force of technological progress in our increasingly digital, data- and algorithm-driven world. Integreat develops theories, methods, models and
-
responsibilities (dependent on experience level of applicant) Develop and improve multi-temporal InSAR processing algorithms (e.g., time series analysis, phase unwrapping, noise mitigation, filtering, atmospheric
-
-based methods to achieve personalised and novel outputs. This position will have a particular focus on developing fundamental AI algorithms and methods that can be used in systems for real-time creative
-
a PhD student, you will develop state-of-the-art learning and inference methods to detect and characterize anomalous radio behavior and to design algorithms that remain reliable under practical
-
a PhD student, you will develop state-of-the-art learning and inference methods to detect and characterize anomalous radio behavior and to design algorithms that remain reliable under practical
-
: Develop and apply evolutionary algorithms to jointly optimize both the robot’s morphology and autonomy, and apply quality-diversity methods to discover a wide range of high-performing designs. Work