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knowledge within the realm of political science. They should be proficient in conducting quantitative analyses. Experience with large language models, machine learning, and/or programming in R or equivalent
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disciplines, including human-robot interaction, robot learning, soft robotics, computer vision, and agricultural robotics. About the PhD project: We are looking for a highly motivated and talented PhD research
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. These experiments will be repeated for a database of events covering different sea ice types, conditions, locations, and rates of ice deformation (from docile to violent). Machine learning techniques will then be
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(or equivalent) in Computer Science, Machine Learning, Mathematics, or a related technical field. For Postdoctoral Fellows: A completed PhD in one of the fields mentioned above and a strong publication record
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should be proficient in conducting quantitative analyses. Experience with large language models, machine learning, and/or programming in R or equivalent programs is an advantage but not a requirement. The
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analysis, machine learning, and interactive and collaborative systems. The prospective PhD candidate will work in close cooperation with staff and our current PhD students. PhD research fellows receive
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repeated for a database of events covering different sea ice types, conditions, locations, and rates of ice deformation (from docile to violent). Machine learning techniques will then be used to find a
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the application of rock physics models, Bayesian inversion methods, and machine learning algorithms in the electromagnetic context. Qualifications and personal qualities: Applicants must hold a master’s degree (or
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proficient in conducting quantitative analyses. Experience with large language models, machine learning, and/or programming in R or equivalent programs is an advantage but not a requirement. Alongside
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conducting quantitative analyses. Experience with large language models, machine learning, and/or programming in R or equivalent programs is an advantage but not a requirement. The evaluation of applicants