52 algorithm-"Multiple"-"U"-"Simons-Foundation"-"Prof" "UNIS" positions at Cranfield University
Sort by
Refine Your Search
-
, integrity-aware multi-domain navigation benchmark and associated algorithms, tested in realistic operational environments. The outputs will support standardisation efforts, accelerate cross-domain navigation
-
development, human-computer interaction, data analytics, user experience design, remote monitoring systems, energy optimization algorithms, and environmental impact modeling. Human-centric AI-driven sanitation
-
—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
-
sensors, firmware-controlled automation, wireless connectivity, and maintenance algorithms. Students will design, build, and test smart sanitation solutions that can monitor system performance, optimize
-
sustainability. The research will delve into power-aware computing strategies, thermal management, and the development of algorithms that balance performance with energy consumption. Students will aim to create
-
-critical systems. The research will focus on developing AI-powered verification tools, health monitoring algorithms, and compliance assurance techniques that ensure system reliability throughout
-
—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
-
from such machines to derive algorithms expressing their state of health and next maintenance needs. A background in both engineering and machine learning would be useful, although help is readily
-
analytics, anomaly detection, and embedded redundancy to enhance system resilience. Students will focus on creating adaptive algorithms and hardware implementations that enable real-time diagnostics and
-
from motion blur, defocus, and imaging artefacts, which hinder accurate diagnosis. This project aims to restore image clarity by designing intelligent algorithms that recover fine anatomical details