43 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" uni jobs at University of Sheffield in United Kingdom
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Forecasting the Future of Biodiversity: Cutting-Edge Approaches to Population and Community Dynamics
: How can tools like passive bioacoustics revolutionize wildlife monitoring? We offer cutting-edge training in statistical modelling, machine learning, and ecological forecasting, and our lab works across
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-standard queries. Essential Application/interview Good understanding of computer operating systems (Windows and Mac OS) and desktop software (MS Office, web browsers) and an interest in learning new
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Machine Learning techniques. As Research Associate you will have a research leadership role in the group, and will assist in day-to-day supervision of post-graduate research students. You will collaborate
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of the resultant analysis. This will also involve the collection of a curated data set, and the use of Machine learning tools to further enhance the analytical process. Together, this will help expand the use
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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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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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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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methods and the potential to develop pioneering reconstruction and calibration techniques involving machine learning. The PhD will prepare equally well for a career in industry and academia. The candidate
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of dark matter particles in the decay of the gluinos. The search will be performed using the full ATLAS Run-3 13.6 TeV proton-proton collision data. The student will gain expertise in machine learning and
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survival is shaped by resource availability, competition, and cultural knowledge of food resources. You will work with an established bioacoustic dataset, a validated call machine-learning classifier, and a