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Field
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participate in developing algorithms for tau lepton identification, and will also have the opportunity to assist with silicon module construction for the ATLAS tracker upgrade. Instructions for applying can be
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-disciplinary research environment Desirable criteria 1. Experience in devising and developing novel machine learning algorithms 2. Hands on experience with ROS and physical robots 3. Excellent
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programmes. The Computer Science programme is focused on software engineering, with modules in Software Engineering, Software Project Management, Data Structures and Algorithms and Data Base Systems. The
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Machine Learning for both supervised and unsupervised algorithms. Deep understanding of principles and best practice in machine learning, with a focus on NLP especially in sequence labelling tasks based
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diabetes and prediabetes by analysing voice patterns, providing a non-invasive and innovative method for early diagnosis. Specifically, this project will develop novel deep learning algorithms, and audio and
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analysis algorithms for the observation and interpretation of existing and new spectroscopic data of exoplanet atmospheres. Experience on cloud/haze microphysics modelling and large scale simulations is
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algorithms. These algorithms act as perfect digital lenses, with no image degradation from aberrations, and provide a fantastically detailed, information-rich view of any sample being imaged. Applications
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Experience with machine learning algorithms and ideally experience developing novel methods Understanding of basic biological principles and experience interpreting ‘omics data Ability to analyse information
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photorealistic game worlds. To achieve this goal, we need advances in many areas, from light transport, sampling, geometry and material representations, and computationally efficient algorithms to display
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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