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Application documents: 1) Brief cover letter, explaining your motivation for applying, 2) Detailed curriculum vitae (including your email address), 3) Complete transcript of grades from all your university-level studies. We do not ask for more information/documents at this point (but you can...
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This PhD research aims to develop and evaluate explainable AI and machine-learning approaches for early detection, risk stratification and prognostic prediction of colorectal cancer, with a focus on
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) to improve cardiovascular risk assessment and prediction. Research Aim This PhD research aims to develop and evaluate AI and Machine Learning approaches for early prediction, risk stratification and prognostic
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for Artificial Intelligence (AI) and Machine Learning (ML) to support earlier and more personalised healthcare. Research Aim This PhD research aims to develop advanced AI and Machine Learning methods
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-based, and machine-learning approaches - Identifying markers of intelligent, intentional, and malicious manipulations of detection systems - Developing detection and classification methods to distinguish
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data provides opportunities for advanced Machine Learning (ML) approaches. Research Aim This PhD research aims to develop advanced Machine Learning methods for prediction, risk stratification, clinical
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therefore work in a highly interdisciplinary environment spanning machine learning, speech and audio processing, computer vision, respiratory physiology and clinical medicine. You should have a PhD, or
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and illegal logging detection. Working at the intersection of computer vision, deep learning, geospatial analysis and remote sensing, the postholder will collaborate closely with academic and
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at developing methodological contributions at the intersection of computer vision, multimodal learning, predictive world models, embodied AI, and human-robot interaction. The candidate will work towards models
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network (MINDnet)”. The PhD project “Efficient learning algorithms for closed-loop optogenetic control of neural circuits” aims to develop an optoelectronic interface with neural circuits, that optically