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. Familiarity with machine learning and proficiency in Python or MATLAB. Excellent communication skills; proficiency in Dutch is desirable but not required. The capacity to thrive in a complex and dynamic
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Vacancies PhD Position in Algorithmic Energy Trading Key takeaways In recent years, the energy sector has undergone changes that have a high impact on the dynamics in power markets. One
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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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(agent-based modeling, differential equations) or machine learning tools. Good programming skills in one of the following programming languages: R, Python, MATLAB, or similar; Excellent English language
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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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that activity-silent mechanisms, such as short-term synaptic plasticity, also play an important role. We will experimentally target these two mechanisms, using EEG in combination with machine learning to reveal
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described in the project overview. Owing to the current composition of the project team, there will be a mild preference for candidates opting for project 2 on “Models and machine learning”. An explanation
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UC Berkeley after obtaining her PhD from the University of Amsterdam for which she did research at MIT and Sigma Computing. Her general research interest is on the intersection of machine learning
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of Amsterdam. Interested in developing fundamental machine learning techniques for tabular data to democratize insights from high-value structured data? Then this fully-funded 4-year PhD position starting Fall
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you eager to make AI more sustainable? As a PhD Candidate, you will develop innovative methods for predicting and reducing the energy consumption of large-scale AI systems during their design phase