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to test the current algorithm and inform development of future algorithm refinements aimed at supporting diabetic foot ulcer (DFU) prevention through identification of temperature differences of > 2.2°C
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that the solutions provided are correct. It will involve a mix of algorithm engineering and formal methods, alongside more traditional software engineering activities. This project involves developing software which
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package Molly.jl on both CPU and GPU, as well as addressing relevant computational and algorithmic questions. This project is part of the Blue Sky Collaboration between the LMB and AstraZeneca, and will
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and Applications of Algorithms” at the Faculty of Computer Science. The position is limited to six months and is planned to be filled from 01.10.2025. Your future tasks: Participation in research
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-dimensional digital twin of the atmosphere using a ground-based array of stereo cameras and sensors. The post-holder will contribute across the research lifecycle from dataset curation to the design of novel
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wearable devices into the existing remoting monitoring system, and the integration of algorithms for automatic analysis of data received at the backend. About You You should hold a MSC degree in a relevant
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will play a key role in the development and production of advanced optoelectronic devices for applications such as quantum technologies, integrated optical sensors, and laser optics. You’ll be supporting
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of algorithms for automatic analysis of data received at the backend. About You You should hold a MSC degree in a relevant field, and have experience of web development, SQL or NoSQL database management systems
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Design of a Fault Detection System for AI-Assisted Adversarial Attacks on Industrial Control Systems
learning. The research will explore how AI-enabled adversaries manipulate ICS environments (e.g. robotic arms, sensor networks) and develop robust detection and response frameworks. By combining real-world
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, and use smart phone apps to collect passive and active data using a prospective observational cohort study design. We will use this data to develop and validate a personalised risk prediction algorithm