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technical knowledge and hands-on experience in: Deep learning frameworks (e.g., PyTorch, TensorFlow) Deep learning models (e.g., YOLO, U-Net, EfficientNet, ResNet, FPN, Fast R-CNN) Computer vision techniques
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as posters Deal with problems that may affect the achievement of research objectives and deadlines. This might include working with CRN networks to ensure recruitment target is met Carry out
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and visits to the UK Met Office. HEPPI-ML is one out of several WCSSP-India projects and joint meetings will provide an opportunity for further networking. The successful candidate will hold a PhD, or
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Duties The responsibilities may include some but not all of the responsibilities outlined below. Implement and test different Artificial Neural Network (ANN) architectures, such as convolutional and
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battery supply chains, to join a successful team at the University of Birmingham. In line with the principles of Net Zero Pollution, the primary aim of this role is to advance understanding of how a
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to deliver an integrated systems approach to energy geoscience that will meet Net Zero goals. Please note that this post may be suitable for sponsorship under the Skilled Worker visa route but first
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(www.c4ts.qmul.ac.uk ) provides the framework for trauma sciences research that we believe will lead to a step-change in outcomes for trauma patients. We are also a member of the International Trauma Research Network
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-life environments. The Role: As Research Fellow on the COG-MHEAR project, you will have the opportunity to use your strong background in deep neural networks and multimodal hearing-aid signal processing
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considered on a pro-rata basis. You will have access to mentoring, career development and networking across the University and beyond. The successful candidate will work under the supervision of Dr Dawn-Marie
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of sewer network and overflows to support effective management, and develop strategies to control pollutions at sources. The post will include delivering research outputs in the form of weekly reports