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benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: ● Research and develop novel reliable deep learning computer vision algorithms for the detection and quantification of GIM lesions
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uses long timescale molecular dynamics (MD) simulations, integrated with experimental observables (especially cryo-electron microscopy data), and machine learning tools to better capture the dynamics
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nonprofits to use machine learning and data science to modernize the public sector. We are an interdisciplinary team of data scientists, social scientists, engineers, and lawyers who are passionate about
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demand. Responsibilities Apply machine learning techniques, statistical modelling, and chemometric methods to extract meaningful biological insights from multivariate data and complex GCxGC-TOFMS datasets
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London and Imperial College Healthcare NHS Trust (ICHT). The project aims to transform the clinical use of electroencephalography (EEG) by developing and validating machine learning (ML) approaches
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of the state of the art in machine learning for generation of artificial data; - identify and select the appropriate methods for the study in question; - develop the research capacity through the application
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related to staff position within a Research Infrastructure? No Offer Description We are seeking to appoint a Postdoctoral Researcher for a three-year position in machine learning emulators of ice-ocean
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- “Towards digital biomanufacturing – developing physics-informed machine learning framework for the advanced multi-modular 3D bioprinting system”. Qualifications Applicants should have: (a) a doctoral
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equivalent. Strong background in machine learning and computer vision. Prior experience in data-efficient classification, synthesis, and detection is preferable. Strong publication records in top-tier machine
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, output validation and reporting. Developing integrative strategies for a diverse set of data, integrating the outcomes to inform future projected trend analysis. Applying statistical and machine learning