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skills and experience: Essential criteria PhD qualified in relevant subject area* Experience developing deep learning segmentation models Experience with Pytorch, MONAI, CUDA or equivalent software
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or Computing – awarded or near completion* Display excellent knowledge of cortical neuroanatomy Programming experience in Python Experience with machine learning - particularly normative modelling
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postgraduate programmes to military and civil service students, responding to the ever-evolving needs of military education. Our teaching equips professionals with the knowledge, creativity and intellectual
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bioinformatics Previous experience with AI and/or machine learning approaches Interest in reproductive health and/or development of clinical tools and algorithms Downloading a copy of our Job Description Full
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expected to contribute to the effective delivery of teaching, learning, and student support by: Delivering and evaluating classroom and practical teaching across modules Designing and supervising MSc-level
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, Bayesian Statistics with a focus on nonparametric methods, Bayesian Computational Methods, Extreme Value Theory, Biostatistics, Probabilistic machine learning, Medical sciences and engineering applications
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spatial transcriptomics and imaging genomics projects, integrating bulk and single-cell RNA-seq datasets, and applying advanced statistical and machine-learning methods (AI/ML) to extract novel biological
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-quality robotics research in the areas of robot grasping and manipulation, kinematics and mechanisms, sensing, and human-robot interaction. Within CORE, SAIR focuses on multimodal machine learning for human
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, Nutritional Sciences and Women's Health cluster) for REF was rated as world-leading or internationally excellent. We use this expertise to teach the next generation of health professionals and research
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the role Overview of the role We are seeking a highly motivated Research Fellow in Machine Learning to join the PharosAI team, focusing on developing novel machine learning methods in computer vision