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(e.g. Python, R) Experience in the use of neuroimaging analysis (fMRI, MRI) to study mechanisms of brain function Previous experience of using Bayesian methods in both model development and fitting
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of using Bayesian methods in both model development and fitting. Previous experience and knowledge of research methods and study design in clinical trials. Knowledge of Good Clinical Practice (GCP) in
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immunocytochemistry, electrophysiology & live cells imaging. The aim of the projects is to approximate cellular phenotypes in an in vitro model of Bipolar Disorder (BD), & attributing abnormal network activity
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computing. You will join the Vision & Human-Robot Interaction (VHR) Group, which brings together researchers working at the intersection of computer vision, robotics, and assistive technologies. The team is
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computing. You will join the Vision & Human-Robot Interaction (VHR) Group, which brings together researchers working at the intersection of computer vision, robotics, and assistive technologies. The team is
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, computer-aided decision support systems Previous experience with using deep learning models (e.g., convolutional neural networks, autoencoders, transformers) for academic research Documented experience in
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, computer-aided decision support systems Previous experience with using deep learning models (e.g., convolutional neural networks, autoencoders, transformers) for academic research Documented experience in
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full-time, fixed-term position for a duration of two years. The role is based within the Department of Computer and Information Sciences at Northumbria University, located in Newcastle upon Tyne. About
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immunocytochemistry, electrophysiology and live cells imaging. The aim of the projects is to approximate cellular phenotypes in an in vitro model of Bipolar Disorder (BD), and attributing abnormal network activity
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product design and operating on computer-aided design CAD software e.g. Fusion 3D Experience in additive manufacturing particularly vat polymerization. Downloading a copy of our Job Description Full details