Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- University of Oslo
- UiT The Arctic University of Norway
- University of Bergen
- University of Stavanger
- NTNU Norwegian University of Science and Technology
- OsloMet – Oslo Metropolitan University
- University of Inland Norway
- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
- NTNU - Norwegian University of Science and Technology
- OsloMet - storbyuniversitetet
- University of Oslo;
- 1 more »
- « less
-
Field
-
experience and expertise in web-scale data curation, development of large language models (LLMs), and in-depth LLM evaluation. LTG has a strong commitment to open-source resource and software development
-
dehydrogenation reactions. The successful candidate will select and synthesise ligands and organometallic complexes from the library, including pincer ligands, and evaluate their catalytic performance in
-
circuit-level simulation, system modeling, and in-silicon hardware prototyping to evaluate approaches against performance metrics such as energy efficiency, inference accuracy and computational latency
-
to assess system vulnerabilities in a controlled and ethical manner, and design and evaluate detection capabilities, including intrusion detection mechanisms, to identify and mitigate cyber threats
-
-resolution, high-speed, and deep 3D quantitative imaging. In collaboration with the Department of Clinical Medicine (UiT), the system will be evaluated for dynamic imaging of cardiac activity in engineered
-
single dataset and potentially misleading validation metrics, and robustness is seldom evaluated systematically (e.g., via stability assessments). By varying key properties of the data-generating process
-
communication skills in English (see https://www.mn.uio.no/english/research/phd/regulations/regulations.html#toc8 ) Desired qualifications: Although not being strict requirements, the following qualification
-
project aims to establish comprehensive benchmarking frameworks for evaluating robotic capabilities in open-world navigation and whole-body (co-)manipulation tasks. By defining standardized metrics and
-
reconstruction algorithms, enabling high-resolution, high-speed, and deep 3D quantitative imaging. In collaboration with the Department of Clinical Medicine (UiT), the system will be evaluated for dynamic imaging
-
mass loss through sublimation and snow redistribution. The PhD candidate will develop/test model parameterizations constrained and evaluated using field observations. The candidate will lead a field