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the FGGA. Together with the researchers at FGGA, experts from central research support services (University Library, Vienna University Computer Center, Research Services and Career Development), as
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familiarity with machine learning and dimension reduction methods are essential. You will demonstrate strong research output, excellent communication skills, the ability to work both independently and
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hardware-aware training methodologies optimized for inference with the architecture and collaborate with project partners involved in the experimental demonstrations of various Machine Learning use cases in
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The University of London The University of London is the UK’s largest provider of international distance and online learning and the convenor of a federation of 17 London-based universities, many
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environments such as slurm; Experience with bioinformatic pipeline libraries such as nextflow; Peer reviewed papers in RNA biology; Experience with LLMs and other machine learning methodologies; Experience with
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, physical layer design, machine learning, and their applications to wireless communications. The successful candidate will also contribute to the formulation and submission of high-quality research
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postgraduate programmes to military and civil service students, responding to the ever-evolving needs of military education. Our teaching equips professionals with the knowledge, creativity and intellectual
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using machine learning techniques. You will be responsible for the evaluation of energy consumption for industrial data reconciliation and preparation of process scheduling models, quantification
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is knowledge of User Requirements gathering and User Interaction, as is experience of developing Apps or commercial software and in AI/ML engineering, including building and deploying machine learning
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June 2026 subject to funding partner decision. The project will focus on scaling-up development our computer vision software for quantitative microscopy, Deep Learning for Time-lapse Analysis (DeLTA