100 data-"https:"-"https:"-"https:"-"https:"-"UNIV"-"Univ" positions at Aalborg University
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
(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
-
project and process management, information management and data-driven approaches in the built environment. You will join a dynamic, interdisciplinary research environment and contribute to activities
-
; measurement system characterization, e.g., validating platform performance such as dynamic range, linearity, phase noise and measurement uncertainty; automated test & data acquisition, e.g., using Python/MATLAB
-
University (AAU) in Aalborg. This full-time position offers a unique opportunity to contribute to high-impact research in drones, AI, and human-computer interaction. Successful candidates will join a dynamic
-
the project based on your interests and in collaboration with a leading architectural firm. The candidate is expected to publish in leading Human-Computer Interaction venues. Your competencies You hold a PhD
-
Communication, the Faculty of Social Sciences and Humanities and the Center for Clinical Data Science (CLINDA), Department of Clinical Medicine, the Faculty of Medicine. AI:GENE-XPLAIN develops AI tools
-
qualifications, including participation on committees or boards, participation in organisations and the like. Additional qualifications in relation to the position. References/recommendations. Personal data. You
-
participation on committees or boards, participation in organisations and the like Additional qualifications in relation to the position. References/recommendations Personal data You can read more about the
-
optimization of production systems and supply chains, including digital twins, virtual system validation, process modeling, and data-integrated decision models. Research should explicitly support managerial
-
, 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