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to achieve, at least a 2.1 honours degree or a master’s in a relevant science or engineering related discipline. Applicants should have strong background in Machine Learning and Deep Learning. To apply, please
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cobalt-free cathodes. The project can involve aspects of materials synthesis, x-ray diffraction and crystallography, scientific software development and machine-learning enhanced analysis depending
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-speed cameras (in a newly renovated lab dedicated to our research group). A significant component of the analysis will include image processing, including data-driven methods and machine learning. You
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about computer data analysis and willing to learn. Laboratory training will be provided but a steady hand is needed for accurate small volume pipetting. You will be working in a team and expected to
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environments such as low light, heat haze, and adverse weather is significantly difficult. These conditions not only degrade video quality but also complicate interpretation by humans and machines, making post
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Appropriate computational skills and knowledge of programming languages (Python, C++, etc.) Experience with Machine and Deep Learning models and software (Keras, Scikit-Learn, Convolutional Neural Networks, etc
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., health and climate/environmental data) and could include a range of data science methods, such as utilising geographical information systems (GIS), statistical analysis, machine learning, deep learning
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Master’s degree in a relevant discipline (cognitive neuroscience, neuroscience, computational neuroscience, psychology, cognitive science, machine learning/data science/AI). Start date: 1 October 2025
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techniques from optimization and control theory, scientific machine learning, and partial differential equations to create a new approach for data-driven analysis of fluid flows. The successful applicant will
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Technology. Mr Kumar is the module leader for Military Vehicle Dynamics, part of the Military Vehicle Technology MSc, which he teaches in the UK and overseas. He worked on project from the UK Ministry of