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contribute to the development and validation of computationally efficient motor-twin models for permanent magnet synchronous machines. The work will focus on machine modelling, parameter and state estimation
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Start date – 1st March 2027 (latest) Project Description Machining generates large quantities of swarf, with many components losing 60–90% of their material during the machining stage. This swarf
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knowledge for a better world. You will find more information about working at NTNU and the application process here. About the position We have a vacancy for a PhD candidate in machine learning
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” Project Scope and Research Questions This doctoral project will explore the relationships between military conflict and slavery in the context of the Seven Years’ War (1756-1763), often characterised as the
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develop techniques to tackle the dynamics of these systems both in imaginary and real time. The latter will form a quantum inspired quantum computer emulator that should be able to tackle large systems
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appointment. Job duties Mentoring new PhD students in numerical computational projects. Conducting comprehensive literature reviews in machine learning for subsurface flow and well performance and supporting
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will be responsible for the follow : (full details of duties available from the Job Description) Research Collaboration and engagement You will have completed a PhD in machine learning, computer science
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, gender, gender identity or expression, national or ethnic origin, shared ancestry, age, status as an individual with a disability, military or veteran status, genetic information, or other protected
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Fully Funded PhD Studentship (UK Students Only) Real-Time Sub-THz Electromagnetic Sensing and Machine Learning for Dynamic Particulate Characterization University of Birmingham with support from
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Auditory SCEnes in Humans and Machines), an ERC Synergy project conducted in collaboration with Dr. Bruno Giordano (CNRS, Marseille). NASCE brings together cognitive neuroscience, advanced neuroimaging