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Field
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-of-the-art in SLAM, situational awareness, computer vision, machine learning, robotics, and related fields Developing and implementing innovative solutions, validated through real datasets and experiments
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to support research groups associated with Institute faculty, in areas such as: ● Machine Learning and Computer Vision ● Natural Language Processing and Data Science ● Biomedical Informatics and
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willingness to learn and develop; Teamwork approach, good communication and relational skills; Strong orientation to results, determination, flexibility and aptitude for problem-solving. Furthermore
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considerations. Experience working with machine learning methods for control, perception, or decision-making in physical systems is an advantage. Knowledge of or a passion for sustainable computing
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-electron Schrödinger equation for fermions and bosons with high accuracy and on the application of these methods to problems in the physics of oxides, semiconductors and their surfaces. Machine learning
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to support research groups associated with Institute faculty, in areas such as: ● Machine Learning and Computer Vision ● Natural Language Processing and Data Science ● Biomedical Informatics and
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inequalities Markov processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic
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qualifications include: Experience with radio interferometric observing, data processing, and imaging. Experience with modern machine learning / deep learning techniques and software packages. Experience with time
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-centred AI applications. This position is highly interdisciplinary as it supports the advancement of data visualisation, machine learning, and artificial intelligence domains. The Post-Doctoral Researcher
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Postdoctoral Research Associate in Global Environment Modelling of Soil Organic and Inorganic Carbon
. The project is aimed to improve our in-house developed process-based computer model and use it to represent the soil ecohydrological and biogeochemical interactions across various carbon and nitrogen soil pools