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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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, machine learning, mathematical modelling, or a related field, to join our research team in the Department of Applied Health Sciences. The successful candidate will work on an NIHR funded methodology project
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John Williamson, and Dr Sebastian Stein. The job requires the proven ability to develop novel theory and build and evaluate working interactive prototypes involving complex computational models
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methods for use across developmental biology and more widely. Current activity involves work on the following aspects: development of new techniques for assessing and modelling the states and dynamics
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modelling and computer simulation to study the earliest stages of embryogenesis in mammals. This full-time post in the group of Dr David Richards at the Living Systems Institute (http://projects.exeter.ac.uk
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We are seeking a Research Fellow to perform research on deployment of machine-learned models for health analytics on distributed IoT/edge/cloud systems using transprecise computing and contribute
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written and verbal communication skills, experience with developing and implementing Bayesian statistical models, and be proficient in computer programming in e.g. R or Python, and C/C++. Please ensure you
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, specifically modelling burrowing behaviour and its impact on the skull. Responsibilities include conducting a range of computer simulations using discrete element and finite element methods, as
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launched Oxford Programme for Cyber and Technology Policy (OxCTP). Reporting to the Co-Directors of OxCTP, you will manage your own academic research activities and collaborate in the preparation of research
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. Using our modelling frameworks which capture metabolic and gene expression constraints and recently benchmarked computational tools for systems identification and model calibration, you will develop new