Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- University of Oslo
- NTNU Norwegian University of Science and Technology
- University of Bergen
- UiT The Arctic University of Norway
- NTNU - Norwegian University of Science and Technology
- University of Inland Norway
- University of Stavanger
- Norwegian University of Life Sciences (NMBU)
- NORCE Norwegian Research Centre
- Western Norway University of Applied Sciences
- BI Norwegian Business School
- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
- OsloMet - storbyuniversitetet
- OsloMet – Oslo Metropolitan University
- 4 more »
- « less
-
Field
-
RITMO. The project, GROOVE, aims to significantly advance knowledge on groove and why specific combinations of rhythmic patterns reliably elicit pleasure and the urge to move. Building on recent work in
-
combines research-oriented bioinformatics with scientific pipeline and software development. The selected candidate will contribute to analyses of large-scale genomics datasets and support the development
-
combines expertise from computational sciences and chemistry to pharmacy and medicine. The convergence environment will include three PhD positions and one postdoc position. The Postdoctoral position within
-
programme Is the Job related to staff position within a Research Infrastructure? No Offer Description With a rapidly changing climate combined with increased use of pesticides, it is imperative to understand
-
understanding of neural codes for time and their relation to memory deficits in patients. The project combines intracranial electrophysiological recordings in humans with behavioral experiments and has three
-
neuromorphic mixed-signal/near-analog circuits for next generation edge-AI systems. You will gain skills in custom chip design, artificial neural networks and edge-AI system implementation. The work combines
-
traits, combining different sources of information, and assessing how environmental effects and management actions affect population dynamics and viability. Available data include long term capture
-
interests through elective courses and secondments. • Blended Learning Approach: Our training combines intensive in-person workshops at partner institutions with regular interactive online seminars, journal
-
for simulation and modeling of wave dynamics, and for uncertainty quantification of extreme events. The project will combine stochastic mathematical models of wave physics with advanced computational methods
-
societal reactions interacted drawing on the combined expertise of the natural sciences and the humanities linking past impacts to future challenges. The project collaborates closely with several other