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Postdoctoral Research Associate in Forest Resilience, Climate Change, and Human Health in the Amazon
holder will also co-supervise a PhD student who will be involved in the same project. This is a highly interdisciplinary project combining forest ecology, remote sensing, machine learning, epidemiology
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Postdoctoral Research Associate in Forest Resilience, Climate Change, and Human Health in the Amazon
illnesses. The post holder will also co-supervise a PhD student who will be involved in the same project. This is a highly interdisciplinary project combining forest ecology, remote sensing, machine learning
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Postdoctoral Researcher in Machine Learning of Isomerization in Porous Molecular Framework Materials
broad range of applications. Computational chemistry and Machine Learning increasingly underlies MFM research to search or screen candidate MFMs prior to synthesis. A major drawback when applying
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discipline (eg Statistics, Machine Learning, Biostatistics, AI, Engineering) with experience of developing and applying new methods. You will be able to develop research projects, with publications in peer
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students and PhD students. Applicants will have, or be close to completing a PhD in a relevant field and possess relevant experience, in the area of probability or statistical machine learning. They will
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area, with content covering robotics and machine learning, and excellent programming skills in Python. You should have research experience in either robotics or machine learning. You should also have
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papers with the other team members. What we are looking for: You must have a master’s degree in a relevant area, with content covering robotics and machine learning, and excellent programming skills in
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of original machine-learning based algorithms and models for multi-modal ultrasound guidance that are intuitive for a non-specialist to use while scanning and trustworthy. You will work with clinical domain
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Agency (ARIA). The PROTECT project (Probabilistic Forecasting of Climate Tipping Points) brings together cutting-edge AI, statistical, and machine learning techniques with climate modelling, aiming
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students and PhD students. Applicants will have, or be close to completing a PhD in a relevant field and possess relevant experience, in the area of probability or statistical machine learning. They will