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both on the sequence and structural level, developing and employing machine-learning tools for predicting antibody-epitope binding. In silico antibody design is a long-standing computational and
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of Anomalies ” (SODA), newly funded by the Norwegian Research Council and affiliated with Integreat – the Norwegian Centre for Knowledge-driven Machine Learning. We are looking for a motivated candidate, who
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for evaluation by the closing date. Only applicants with an approved doctoral thesis and public defence are eligible for appointment Strong programming and artificial intelligence/machine learning skills Interest
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development for a hard-working candidate. Main responsibilities Develop and apply machine learning and statistical modeling techniques, including novel AI architectures, for the analysis of complex traits and
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– the Norwegian Centre for Knowledge-driven Machine Learning. We are looking for a motivated candidate, who has interest in both theoretical, methodological and applied research in anomaly detection in sequential
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performance, plume evolution, and pressure-build ups in potential multi-site storage licenses. The research will help to suggest best practices for machine learning integration in de-risking CO2 storage sites
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the Job related to staff position within a Research Infrastructure? No Offer Description The position is in the Digital Signal Processing and Image Analysis (DSB) research group, Section for Machine
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. • Experience with machine learning and artificial intelligence. • Strong programming skills (e.g., Python, C++), and familiarity with ROS or similar frameworks. • Experience with simulation tools like
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measurement quality issues related to respondent non-compliance in ecological momentary assessment or exploring the use of machine learning techniques to aid the estimation of item response theory (IRT) models
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for imaging Apply for this job See advertisement About the position Position as PhD Research Fellow in machine learning available at Department for Informatics with the research group Digital Signal Processing