Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
collaboration skills. Effective analytical and problem-solving abilities. Ability to manage multiple projects and meet deadlines. Proficiency in research methodologies and data analysis. Ability to work
-
perception, decentralization and mission execution. The RAI team has a strong European participation in multiple R&D&I projects, while RAI was also participating in the DARPA SUB-T challenge with the CoSTAR
-
combined with soil sensors systems and UAVs with multispectral cameras. Your tasks in detail: Development and application of high resolution time-lapse GPR and EMI imaging methods at multiple scales
-
their performance for a range of applications. A focus will lie on quantum algorithms for many-body systems, in particular on classical shadows. Here, you will also transfer results for qubits to fermions
-
Description About us: LMU Munich is one of Europe’s leading research institutions. Scientists from all over the world encounter excellent conditions for their work - in their own research field and
-
—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient
-
Job no:516615 Work type:Fixed term - Part-time Campus:Adelaide Categories:Level A, Level B (Level A/B) $78,544 to $131,335 per annum plus an employer contribution of 17% superannuation applies
-
of mobility dedication and enjoyment of independent work as well as the further development of your own skills team spirit and fair and open communication skills very good knowledge of German and English We
-
skilled human operators must acquire and integrate information from multiple distributed sources (e.g., physical and informational environments) to coordinate cognitively (e.g., decision-making) and
-
on previous research at Cranfield, which has demonstrated the benefits, the project investigates the impact of various porous structures on aerodynamic performance. Focus is placed on the entire incompressible