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, electrical & electronic engineering, or equivalent. Background knowledge in signal representation/processing, visual data compression, and data-driven and machine learning/analysis. Prior research experience
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: Developing and deploying machine learning models (e.g. graph neural networks, neural force fields, diffusion models) for molecular property prediction and molecular generation. Integrating quantum chemistry
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programming language Experience with statistical inference or machine learning methods (e.g. ABC, Bayesian modelling) A proven publication record with at least one first author publication in a peer-reviewed
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. • The ability to work independently and collaboratively within a multidisciplinary team. • Strong writing, critical thinking, communication, and presentation skills. • Experience in Machine Learning is a
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technologies Artificial Intelligence and Machine Learning applications Computer Vision and sensor integration for agricultural applications Human-Robot Interaction in agricultural contexts Robotic Perception and
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who shares our values and who will support the mission of the university through their work. Qualifications: Ph.D. in a relevant field such as Learning Sciences, Human-Computer Interaction, Education
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PROGRAMME AND TRAINING: - extend the knowledge of the state of the art in machine learning for lung cancer imaging data; - identify and select the appropriate methods for the study in question; - develop
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following mandatory requirements: a) A completed degree in Computer Engineering; b) Good knowledge in the areas of Machine Learning, Natural Language Models, and Computer Security – information to be provided
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or translational research experience Knowledge of machine learning, Bayesian modeling, or statistical method development Ideal Personal Attributes: Independent, proactive, and scientifically curious Detail-oriented
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of how this machine functions. Elucidating the function is key to unlocking why certain mutations can cause disease such as early onset cardiac disease (through the muscle myosin protein) and how small