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& robust control, and learning for dynamics & control. The main task of the PhD student will be to develop sound data-driven methodologies for learning control policies with provable guarantees
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. For further information please contact Professor Nicola Walsh (Nicola.walsh@uwe.ac.uk) or Professor Sarah Voss (sarah.voss@uwe.ac.uk). For an informal discussion about the studentship, please email Professor
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profound interest in inorganic chemistry, in both experimental and modelling applications. We are looking for candidates who are also interested in the analytical and numerical aspects of the work to support
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interpretation of platform data, stakeholder feedback, and project outcomes; maintain records and databases; and draft progress reports, technical reports, and academic publications. Contribute to the design
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This self-funded PhD opportunity sits at the intersection of several research domains: multi-modal positioning, navigation and timing (PNT) systems, AI-enhanced data analytics and signal processing
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Systems, or a related field. Strong analytical and critical thinking skills. Strong machine learning (ML), computer vision (CV), large language models (LLM) for quantitative data, texts, images, and sensor
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systems theory Excellent analytical and problem-solving skills Desirable criteria Advanced programming and data analysis skills Computational neuroscience background Behavioral data analysis skills Strong
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Contract type: Full time (35 hours - 1FTE), fixed term (18 months) Detailed description The recruited candidate will be responsible for generating a database of qualitative data acquired through
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-3413 ), 4-Limited flight data for adaptive methods (doi.org/10.1016/j.geits.2022.100028 ), and 5- Failure to use a robust state estimator to increase robustness of EMS in eVTOL, have not been filled by
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of heterogeneous catalysis General knowledge of homogenous catalysis Experience in reactor operations for homogenous and/or heterogenous catalytic systems Experience in solvent handling and gas and liquid analytical