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per year for 3.5 years. Lead Supervisor’s full name & email address Dr Massimiliano Fasi: m.fasi@leeds.ac.uk Project summary The growing importance of artificial intelligence is fostering a paradigm
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Excellent oral and written communication skills in English Strong problem-solving abilities Interdisciplinary computer science interests Ability to work independently and in a collaborative environment
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, there is no consensus on the adsorption mechanisms of these molecules on the metallic surfaces. In this PhD project we will use state-of-art molecular simulation methods [2,3] to clarify the adsorption and
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PhD project (such as mathematics or theoretical physics) is our standard entry, however we place value on prior experience, enthusiasm for research, and the ability to think and work independently
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access to an NWSSDTP Research Training Support Grant for eligible research expenses. Application process Applications for this ESRC CASE PhD Studentship should be sent by email to the School of Law and
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of control theory and optimization. Knowledge of partial differential equations. Have a strong coding ability Research Associate: Hold a PhD in Engineering, Mathematics or a closely related discipline, or
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. select 'PhD Electrical and Electronic Engineering (full time)' as the programme of study You will then need to provide the following information in the ‘Further Details’ section: a ‘Personal Statement
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PhD project (such as Electrical Engineering or Computer Science) is our standard entry, however we place value on prior experience, enthusiasm for research, and the ability to think and work
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to the commencement of the PhD. Vision We are seeking for a highly motivated PhD student to conduct cutting edge research of the AI techniques that will power future flexible manufacturing systems. Together, we will
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flexible working hours. Upon agreement, hybrid working hours within Austria might be possible up to a certain extent. Internal further training & Coaching: Opportunity to deepen your skills on an ongoing