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Field
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neurobiology and mouse models is advantageous. Have experience with in vivo calcium imaging (preferably 2-photon), stereotactic surgery and drug delivery, gene expression analysis (e.g. snRNAseq) and antisense
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requirements: PhD degree in Computer Science, Electrical and Electronic Engineering, or related field. At least 3 years of relevant experience in computer vision, artificial intelligence, etc. Proficiency in
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. To set up and analyze experiments and datasets under different conditions. To propose a methodology/framework in a software prototype to be developed in the project. To report research findings in the form
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of imaging protocols (MRI, MRS, OPM-MEG). Candidates will benefit from a demonstrable experience in these fields. The core abilities and attributes required include resilience, creative problem-solving
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; experience of working on biological systems and/or craniofacial system; experience in image processing and material characterisation. The post is initially funded for 3 years and will be subject to standard
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models using frameworks such as PyTorch and TensorFlow. Research experience in medical image analysis using deep learning algorithms. Strong track record in machine learning, computer vision, and medical
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imaging support researchers. Islet Biology is a growing focus, particularly with recent recruitments and infrastructure support through the Canada Excellence Research Chair in the Islet Microenvironment
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The Postdoctoral Research Fellow will contribute to a range of research and research translation activities as part of an Australia Economic Accelerator funded project developing a prototype using Large Language
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for clinical AI based on patient data from heterogeneous sources notably language/speech-based sources. The activity will focus on the development of a prototype implementation of early warning- and other AI
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able to plan and conduct your own work independently, whilst also being able to build relationships and collaborate with others. A PhD (or near to completion) in human metabolic physiology, nutrition