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The opportunity The University of Liverpool is a key partner in a £14 million initiative (https://tinyurl.com/yc5z768m) to develop a sustainable, next-generation manufacturing facility, using
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, including deep reinforcement learning, large language models, and the theory of deep learning. The candidate will develop DRL algorithms for online and off-line tasks, for robotic applications and possibly
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power system simulation Energy management system (EMS) or supervisory control algorithm development Hardware-in-the-loop (HIL) platforms (e.g., OPAL-RT, Typhoon HIL) Experience in battery energy storage
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of human disease through computational and big data-driven approaches. We entail the development of new computational algorithms, statistical/quantitative methods, and combining cutting-edge bioinformatics
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associate will participate in the design and implementation of the reference data model to ensure simulation system interoperability. Additionally, they will develop AI algorithms and multi-criteria
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candidates must thus have a strong interest in algorithmic development as well as embedded hardware integration. Role and responsibilities This PhD project will be executed in close cooperation with
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project’s principal investigator, Associate Professor Lars Rohwedder, an internationally recognized expert in the areas of approximation algorithms and parameterized algorithms, see https://larsrohwedder.com
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exploratory analysis on large, multi-dimensional datasets; (b) develop predictive/diagnostic models and algorithms to lead and support clinical/translational research; (c) work with cross-functional teams
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industry and international partners. For more details, please view https://www.ntu.edu.sg/atmri . We are looking for a Research Fellow to conduct research on air traffic management (ATM) algorithms and data
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3GPP compliant 5G/6G NR NTN OFDM waveforms Develop and analyse signal processing and/or machine learning algorithms for joint channel, delay, Doppler and carrier phase estimation, remote object ranging