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Field
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framework or knowledge graphs; 2) Uncertainty analysis and risk modelling; 3) Port and maritime operations; 4) Cybersecurity or critical infrastructure protection; and 5) Machine learning and real-time data
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machine learning–guided failure analysis and diagnostic capabilities for hybrid electronics. This position offers an exciting opportunity to work at the forefront of semiconductor technology, with close
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or photogrammetry methods, in combination with data science approaches such as machine learning and data assimilation via cryospheric models. A main focus of this work is snow and glaciers in the mountains around the
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, applying Big Data, Machine Learning and Large Language Model techniques, and developing measures of social connectedness using anonymised data from online platforms. The position is full-time with flexible
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towards better understanding what replication can mean for qualitative research. Last but most topically, the theme of replication raises a host of questions in relation to machine learning and artificial
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degree will definitely be advantageous. Knowledge of machine learning, pytorch, huggingface etc... Knowledge of image processing is required. Ability to effectively and efficiently utilise industry
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Staff Union Non-Union Non-Classified Staff Pay Grade Level Grade Level: 99 Pay Grade Range N/A Status Calendar Year, Full-time, Limited Department Information Department Elec, Computer & Bio Engr Contact
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analysis including econometrics, statistics and machine learning and related disciplines handling large amounts of complex data. They should provide evidence of potential for research and publication
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(e.g. reports, policy documents, gray literature, or citizen science observations), Apply advanced statistical, machine learning, and AI techniques to analyze complex datasets and uncover actionable
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theoretical statistics and data science, and is heavily involved in research at the crossing of statistics and machine learning. Modern vessels produce vast amounts of multivariate data streams. The project