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Our group The scientific programmer will be embedded in the Massivizing Computer Systems (MCS) group, which focuses on research in distributed computing systems and ecosystems, and currently spans
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machine learning, big data analysis and advanced computing; One year of post-PhD relevant experience in research or industry will be an advantage; Experience of working in an international environment will
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PhD* in a topic such as animal acoustics, machine learning, quantitative ecology, quantitative biology, signal processing or similar. Evidence of the ability to conduct high-quality research and write
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, together with relevant expertise in areas related to Artificial Intelligence, such as: Foundational Models, Algorithmic Research Machine/Deep Learning Computer Vision Parallel & Distributed Computing Control
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Cancer intraoperatively to facilitate radical resection. Job Responsibilities: As a PhD student, you'll focus on: Develop cutting-edge AI models: Train state-of-the-art deep learning models to segment SCC
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both software and hardware. The chance to work with innovative technologies such as AI/Machine Learning. A pleasant and informal working environment with plenty of room for initiative. Job Requirements A
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will house 2 PhD scholars and 3 Postdoctoral Scholars and will run between 2024-2029. It carries international collaborations and publication programmes, and will maintain a documentational project on
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collection has been the focus of concentrated digitisation efforts during the past eight years, including specimen photography. This new project seeks to harness this dataset using machine learning in order to
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/ESM). Advanced data analysis techniques (e.g., machine learning) will be used to develop algorithms that contribute to the creation of a model for "dynamic stress profiles." The research is grounded in
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, together with relevant expertise in areas related to Artificial Intelligence, such as: Foundational Models, Algorithmic Research Machine/Deep Learning Computer Vision Parallel & Distributed Computing Control