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requested to upload the following documents: A cover letter stating your motivation to apply for the position and your key competencies relevant for this position. An up-to-date CV, including details of your
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: This PhD project will develop model- and data-driven hybrid machine learning material models that capture the complex, nonlinear, path- and history-dependent behaviour of materials. The goal is to create
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in Amsterdam is fully arranged and covered by the internship program. You will also receive a monthly stipend of 1200 euros to help cover your daily expenses. Requirements Include in your application a
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geospatial data on fisheries activities near OWFs to evaluate the distributional impacts of OWFs across different fleet segments; conducting fieldwork and surveys in collaboration with ‘NO REGRETS’ partners
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: This PhD project will develop model- and data-driven hybrid machine learning material models that capture the complex, nonlinear, path- and history-dependent behaviour of materials. The goal is to create
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, analysis, and model choice while retaining strong error guarantees. This means that researchers can adapt their research questions and sampling plans to the data as they come in and in a way that is as model
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exposure, victimisation, and perpetration based on survey and social media data. You will also study developmental processes, potential consequences, and the role of parents in these processes. Your job
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, different designs of AI systems should be assessed during the design phase. Data flow diagrams used at NOLAI capture the processing, storage and transmission of data: key elements in assessing
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redistribute rainfall across the Amazon and thereby affect its internal forest-rainfall feedback. Conversely, changes in forest cover distributions would affect the energy and water balances in the Amazon, which
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localised economic gains. These contrasting findings highlight the current uncertainty surrounding the specific impacts of AMOC weakening on human societies. In this PhD project, you will use models and data