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expertise in machine learning, soil microbiomes, microbial 3D printing and biophysics, our team has access to a broad spectrum of techniques and practical know-how. This is therefore an exciting opportunity
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with core data analysis and professional skills that are necessary for bioscience research and related non-academic careers. https://www.yorkshirebiosciencedtp.ac.uk Project Description: Join an exciting
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. Into the second year, the project moves toward methodology refinement and Machine Learning integration. The student will execute a more ambitious cycle with a complex alloy system and integrate machine learning
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develop our composite machining team. In this pivotal role, you will lead a diverse group of staff, fostering their skills in CNC programming and operation to efficiently undertake research relating
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Accessible Tinnitus Notch Noise Therapy via Machine Learning, Acoustic Metamaterials and Additive Manufacturing (with NHS and TinnitusUK) EPSRC Centre for Doctoral Training in Sustainable Sound
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for MND which could be translated into the clinic. The idea is to use cutting edge machine learning to create clinically actionable predictions such as the time from diagnosis to requirement for a
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other large scale machines (e.g. hydro-electric power stations, ships propeller bearing) sliding type or ‘hydrodynamic’ bearings [4] are much more common. There is increasing interest from industry
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Physics based machine learning algorithm to assess the onset of amplitude modulation in wind turbine noise (with TNEI Group) EPSRC Centre for Doctoral Training in Sustainable Sound Futures PhD
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digital-first principles. By fusing materials science, machine learning, and advanced simulation, the project offers an exciting opportunity to redefine how we engineer and deploy functional surfaces
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work with the UK semiconductor industry. The studentship represent a unique opportunity to be trained in the epitaxy process and to work in an emerging and exciting area of combining AI/machine learning