Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Technical University of Denmark
- Aalborg University
- University of Southern Denmark
- Nature Careers
- Aalborg Universitet
- University of Copenhagen
- Aarhus University
- Technical University Of Denmark
- Copenhagen Business School
- Graduate School of Arts, Aarhus University
- University of Southern Denmark;
- COPENHAGEN BUSINESS SCHOOL
- Danmarks Tekniske Universitet
- NVIDIA Denmark
- University of Birmingham
- 5 more »
- « less
-
Field
-
research on architectures and methods for the real-time delivery of EO data from dense nanosatellite/CubeSat constellations and to develop innovative GNSS-based sensing methods and AI models to detect a
-
the Center for Pharmaceutical Data Science Education (CPDSE) and will be conducted under the supervision of Associate Professor Casper Steinmann . The project concerns physics-based computational modeling
-
underlying gene expression, as well as a clear view of their medical importance and potential for a future research carreer. Information on CGEN can be found at: https://cgen.ku.dk/ Information
-
. Project Description Dynamic assessment of bone and joint motion remains a major challenge in musculoskeletal imaging. While MRI and CT provide high-resolution anatomical information, they are limited in
-
(such as heart disease, diabetes, and cancer) using, for example, data from registries and/or biobanks. The research will be performed in close collaboration with Center for Clinical Data Science (CLINDA
-
the microbial communities responsible for dark carbon fixation at hadal depth. The focus will be on pelagic communities, but aspects of benthic chemosynthesis could be included. For further information please
-
analyses. Integrating eDNA datasets with ecological and environmental data. Participating in fieldwork across Denmark and collaborating with national and international project partners Project description
-
single‑photon detector (SNSPD). Additional responsibilities include developing efficient coupling of free‑space optics to optical fibers, conducting extended data‑taking runs with TES and SNSPD systems
-
, the spatial and temporal resolution of EO data. MASSIV-EO aims to overcome these limitations through foundational research on architectures and methods for the real-time delivery of EO data from dense
-
learning Distributed and federated training The candidate is expected to hold a relevant MSc degree in Computer Science, Data Science, Physics, (Applied) Mathematics, Computational Statistics or another