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About You This research aims to develop and test machine learning models that can recognise specific imaging planes acquired during the first trimester fetal ultrasound scan. This will be the first
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up with the data-driven solutions using advanced data science techniques such as Deep Learning, Machine Learning Algorithms, Natural Language Processing, etc. The Ubicomp lab is looking for a key role on
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, drawing on machine learning where it strengthens these methods. The research supports mission-critical scenarios and feeds into an end-to-end resilience proof of concept developed together with Swedish and
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experimental approaches such as non-coding CRISPR screens, the Massively Parallel Reporter Assay (MPRA), saturation mutagenesis, and synthetic sequence design, alongside machine-learning models of regulatory
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, foundation models for science, scientific machine learning, and AI applications in materials, chemistry, biology, healthcare, simulation, or hypothesis generation; (2) AI for Society, including AI and data
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interest in scientific research, both within and beyond your speciality and across the wider field of statistics and machine learning. Excellent communication and interpersonal skills and be fluent in
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microelectronics through pioneering research in digital design, machine learning hardware, and emerging computing paradigms. Job description The future of healthcare, communication systems and autonomous
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. Qualifications Applicants at Postdoctoral Researcher level should hold a PhD in AI enabled learning, educational technology, information systems, computer supported learning, social entrepreneurship, innovation
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individuals with a wide range of backgrounds and experiences. You should demonstrate: Essential Criteria: Hold, or expect to hold shortly, a PhD in analytical chemistry, mass spectrometry, metabolomics
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computing and/or cloud computing; familiarity with Earth system models through model development, model execution, and/or model performance diagnoses; applied mathematics methods such as machine learning