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Postdoctoral Researcher in Machine Learning of Isomerization in Porous Molecular Framework Materials
for isomerization in MOFs: https://doi.org/10.1039/D3QI01065A What we are looking for: A PhD in Chemistry, Materials Science, Physics or a related field Experience in python (ASE, scikit-learn, pytorch) is essential
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Overview This PhD project will take a comprehensive approach to exploring how corporate sustainability disclosure practices evolve in response to the integration of Machine Learning (ML) within
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for succession planning. The proposed PhD research aims to develop a framework that leverages AI-driven predictive analytics to assess employee skill capabilities, automatically identify skill gaps, and provide
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a person’s learning and career growth. The purpose of this PhD project is to explore whether artificial intelligence can address feedback bias in technology settings. Objectives · To explore if AI can
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departments and roles dedicated to such work. Reports show this approach may not be sustainable (see for example Hicks, 2024). We call for research proposals for a PhD project that studies the interactive
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academia and communities through a holistic program of co-created research that actively engages with public groups. As we strive to establish an innovative approach to conducting PhD research, we seek
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-funded PhD project. See our fees and funding pages for further guidance and ways to fund your project.
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rigorous coding scheme to be used for the evaluation of model-based facilitated workshops. The PhD student will then use this coding scheme to analyse workshop transcripts from previous projects already
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research. The PhD candidate will aim to develop an understanding of existing climate change models and choose or develop a customised model for the purposes of the study. Furthermore, it will involve
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Overview An exciting opportunity has arisen through a 3.5 year, fully funded PhD studentship jointly funded by Kemin Europa and the Perry Foundation; primarily based at the Nottingham Trent