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We invite applications for a full-time Postdoctoral Research Associate to join the new Data-Driven Algorithms for Data Acquisition (DataAcq) project. This is a timely project developing new
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neurosurgical centre. In this role the successful candidate will develop deep learning algorithms & validate models on diverse clinical data which include magnetic resonance imaging (MRI) and computed tomography
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connectome, with a focus on the chemosensory circuits involved in human host-seeking. The principal focus will be on the high level proofreading, annotation and analysis of connectomics data. This will include
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to determine the activators of inflammation in atherosclerosis. You will identify and develop suitable techniques, and apparatus, for the collection and analysis of data (e.g. flow and mass cytometry, confocal
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aims at addressing computational challenges associated with data acquisition and information extraction from complex sensors and sensor networks. Crucially, uncertainty management and quantification
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completion of a PhD in Psychology or a relevant area along with experience of collecting data from research participants. With excellent data analytic skills, you will be familiar with SPSS and at least one
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model and data biases; (2) build and evaluate XAI tools for external auditing and red-teaming; (3) generate predictive explanations without accessing model internal; (4) providing insight into model
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/or growing interest in extreme events, climate change, attribution/causality analysis, epidemiology, public health, ECD, and data science. The Research Associate will be proficient in programming
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atmospheric physics, meteorology, climate, numerical methods, and data science. The Research Associate will be proficient in programming/scripting (e.g., in Python, and/or R, and/or Matlab, and/or Bash script
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suggests that the microbiome can also impact smell, and chemosensing. Preliminary data from the lab have shown that germ-free mice have an impaired olfactory function when compared to conventionally reared