566 postdoc-in-thermal-network-of-the-physical-building PhD positions in United Kingdom
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, classical ecological theories and methods to mathematically model species interactions networks and communities across spatial scales. As part of the project, the student will extend these methods and make
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The Intelli-Ingest Doctoral Network is an EU-funded Marie Skłodowska-Curie Action (MSCA) initiative is a network bringing together leading academic, clinical, and industrial partners to train a new
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the experimental activity. The candidate will be joining a multidisciplinary team in a lab where we design, make and validate materials and structures. This PhD will expose the successful candidate to a
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of Science and Technology (proud member of the Alan Turing University Network) and be supervised by leading experts in machine learning for healthcare. You will also be affiliated to the School of Health
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cross-disciplinary in nature, building skills in molecular biology, bioinformatics, ecological mathematical modelling, algal physiology and cultivation. We are looking for a highly self-motivated
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to Postdocs, Research Assistants, Research and Teaching Technicians, Teaching Fellows and AEP equivalent up to and including grade 7. Visit the Centre for Research Staff Development for more information. About
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About the Project Join the School of Physics and Astronomy at the University of Birmingham for groundbreaking PhD research that aims to improve the knowledge of biological macromolecules
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short courses in the core subjects of this PhD programme including process intensification and green chemistry. This project is part of the Process Industries: Net Zero (PINZ) Centre for Doctoral training
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discussion regarding the PhD. This is an excellent opportunity for an enthusiastic graduate to build a strong skillset in interdisciplinary research and a collaborative network with both academic and
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regulations and product certification due to the inherent uncertainty of how AI systems make decisions. Classical engineering development guidelines, are difficult to interpret or simply not transferrable to AI