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), Deep Neural Networks. Probabilistic Machine Learning and Time-series Analysis. Industrial applications of AI (energy, process industry, automation). Software development experience in teams. Programming
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. Experience working with remote sensing or geospatial data is a requirement Strong programming skills applied to geospatial data, such as satellite data, is a requirement. Experience working with deep learning
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national and international partners. The PhD project will focus on integrating advanced photogrammetric techniques applied to historical aerial imagery with modern deep learning-based image classification
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above. Proficiency in scientific programming (Python) and deep learning frameworks. Fluent oral and written communication skills in English. Desired qualifications: Expertise in broader topics in
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defence are eligible for appointment. Solid background in machine learning and scientific profile relevant to the project described above. Proficiency in scientific programming (Python) and deep learning
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. The plan is for the candidate tofocus on Bayesian modelling in close collabora-tion with researchers at the HISP centre that work on complementary deep learning approaches to disease modelling as
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secondary seal during deep CO2 storage in saline aquifers or depleted oil/gas fields. This may happen as escaped, buoyant CO2 migrates upward through a migration pathway (e.g., permeable pore space, along
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deep CO2 storage in saline aquifers or depleted oil/gas fields. This may happen as escaped, buoyant CO2 migrates upward through a migration pathway (e.g., permeable pore space, along the well bore
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advertisement About the position A position as Researcher in Natural Language Processing (NLP) is available in the Language Technology Group (LTG) within the Section for Machine Learning at the Department
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at the HISP centre that work on complementary deep learning approaches to disease modelling as well as on development of plat-forms for running and evaluating prediction models. The PhD candidate will develop