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Field
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, machine learning, and information-theoretic approaches to achieve robust, non-intrusive security for the ever-expanding IoT landscape. Feature Engineering for Encrypted Traffic: It is crucial to identify
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solutions are not yet evident. There are several aspects that should be considered: The level of AI sophistication in terms of decision-making autonomy and human-machine teaming. The use of logic and data
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essential for candidates to hold a driving licence (incl. an international licence) as the role involves some field sampling around the UK. For further information please contact: Dr Tao Lyu and Prof Bruce
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both as part of a team, and independently, coupled with excellent communication, organisational and problem-solving skills are essential to this role. More information on the role and person
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the PhD. The Faculty has outstanding facilities and works in partnership with leading industrial partners. Please contact Mohammad Reza Ilkhani ezzmi1@exmail.nottingham.ac.uk for further information and an
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will provide training in nanomaterials synthesis, soft matter physics, X-ray scattering, and data-driven experimental design. The student will gain expertise in an emerging area of colloidal science
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-time senior women’s players. The candidate will be responsible for all aspects of the research project, including obtaining ethical approval, data collection and dissemination/communication of research
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partnership with leading industrial partners. Please contact Mohammad Reza Ilkhani ezzmi1@exmail.nottingham.ac.uk for further information and an informal discussion regarding this PhD.
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and empathic behaviours most effectively improve patient outcomes. In this role, you'll conduct NMA, perform data analysis, and contribute to research output. Your work will inform future NIHR funding
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. Funding information: This is an EngD studentship fully funded by the National Physical Laboratory (NPL). The studentship is for 4-years and provides a tax-free stipend of £22,780 per annum including a £2k