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Field
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independently and collaboratively within a team. Applicants must have a PhD in materials science and engineering, chemical engineering, or related field. Excellent experimental and analytical skills relevant
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assist working groups and steering committee members in accomplishing project milestones, training PhD and other students, conducting research and analysis, developing dissemination materials, and
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of PhD), or Research Associate (more than 3 years of PhD). A strong preference is for individuals with (a) computer science or computer engineering degrees with previous experience in natural
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that also act as green energy producers driving the societal transition towards net zero. In this position, you will build on your expertise in IoT and low-power computer and communication systems to research
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systems (ITS). In particular, the successful candidate will conduct cutting-edge research in: Developing physics-informed neural networks (PINNs) for complex dynamical systems modeling and observer design
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buildings closed days (and Christmas Eve when it falls on a weekday) for all full time staff. Use our total rewards calculator: https://www.hw.ac.uk/about/work/total-rewards-calculator.htm to see the value
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and maintain a strong network of national and international collaborators, leveraging diverse expertise to advance research goals. Ensure compliance with all safety regulations and ethical guidelines in
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of natural language processing, machine learning, artificial intelligence, and human-computer interaction. Established within the School of Computer Science, LTI pioneers innovative approaches to understanding
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, computation biology or a related field Preferred Experience/Skills: Experience in graphical network models, data integration. Experience with single-cell RNA seq data. Required Knowledge, Skills and Abilities
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular