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and coordinate with growers, collaborators, and research staff across multiple locations. - Maintain research records and assist with data analysis and reporting. Minimum Qualifications: - Ph.D. in
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future autonomous instrument control and self-directed experimentation will be developed, recognizing the challenge presented by the integration of multiple complex systems. Coding and user interface
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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
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that align with Net Zero targets without compromising torque-speed performance. Aim This PhD project aims to develop a new generation of electric machines optimised for sustainability across the full lifecycle
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History Collections due to the difficulty of conducting fieldwork in this remote region. In this PhD project, we will expand on this dataset, use long-read sequencing to assemble new genomes and employ a
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environment related to advanced reactors and contribute to ongoing activities aligned with your research. Eligibility Open to Home students (full award – home fees plus stipend). There is very limited
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alignment with the project’s coding framework. Conduct comprehensive literature reviews on topics such as refugee student experiences, culturally responsive pedagogy, multilingual language learners (MLLs) and
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aims to develop a novel theoretical framework for nonlinear and robust control of dynamical systems from a phase perspective. You will have the opportunity to freely explore multiple research directions
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experience and how this aligns with the PhD project) evidence of your enthusiasm for, and experience in, multidisciplinary research evidence of your ability to work independently and as part of a team to
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(Agarwal et al., Quant. Sci. Technol. 2024), so that for any verification approach to be useful it needs to go beyond widely employed Markovianity assumptions. This work, directly aligning with NQTP Missions