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/or QGIS) Very good English language skills, both written and spoken Basic knowledge of the German language or the willingness to acquire it for the purpose of knowledge transfer Openness, creativity
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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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Explore opportunities for collaboration with researchers in SPH and across the University to expand and lead research initiatives to support the Collaborative Mentor postdocs and students within
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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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nutrition, such as: analysis of time series data and dynamic processes, where signals and responses evolve over time. statistical modelling, AI, and machine learning on large epidemiological cohorts, diet and
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visits abroad. This international exposure enriches perspectives and fosters cross-cultural learning, ultimately enhancing the quality of research outcomes. BIGS-LF does not offer PhD positions. You need
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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