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(EO) data can be used to assess different facets of ecosystem functioning in grasslands and forests. Within the project, you will collaborate closely with other PhDs and postdocs to collect field data
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student and postdoc who will carry out experimental work, which will allow for validation of the models. You will collaborate with experts from TU Delft, TNO and several large and SME companies involved in
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applications based on the following skillsets. If you do not fullfil all requirements, please still apply (there is room for learning-on-the-job). An engineering degree, preferably, aerospace or mechanical
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meet the requirements for admission to the faculty's doctoral programme in Engineering Cybernetics . Strong programming skills, in particular Python, and practical experience with modern machine learning
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independently. We value personal development: you will receive training in advanced computational techniques, machine learning, data analysis and scientific communication. You’ll have the opportunity to attend
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characterizing individual nanoclusters • Engineering and purify protein nanopores with tailored sensitivity to size, charge, and etc. • Developing data analysis pipelines and machine learning approaches for signal
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cross-disciplinary and focussed on translating technological advances in biomedical engineering towards improving outcomes for cancer patients. PhD students within the group are supported by postdocs
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to express the negator (‘not’) early rather than late in the utterance. You will learn to use multiple methods, including artificial language learning and EEG, collecting data from different language
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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
for the position. Preferred selection criteria Experience with machine learning or other relevant AI technologies Scandinavian language skills Previous experience from industry or research in engineer-to-order
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of dynamic radar scenes. The project combines methodological machine learning research with experiments on real automotive sensor data. You will have access to research vehicles and advanced radar prototypes