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provide intuitive, human-interpretable explanations for complex model predictions derived from Earth Observation data, including high-resolution satellite and aerial imagery. You will engage in a
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for High-Frequency Financial Time-Series Data Introduction Are you passionate about using advanced machine learning techniques to solve real-world problems in financial trading? Do you enjoy working with
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using state-of-the-art measurement systems such as LC-(HR)MS? This might be the next step for you! Pyrrolizidine alkaloids (PAs) are a large and structurally diverse class of plant-derived toxins, with
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proficiency in R or Python for data analysis and modeling. Familiarity with analyzing large-scale healthcare datasets and real-world data. Experience in developing and applying simulation models, including
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, designs, infrastructures and action-perspectives for a climate-proof, drought-resilient, and water-sensitive built environment. For more information about the project, see: Thirsty Cities . Are you eager
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top predators in the North Sea. Key responsibilities: Analyse tracking data of seals and seabirds to investigate their foraging behaviour in relation to dynamic environmental variables, such as tidal
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Your job We are seeking a PhD candidate to drive the transformation of food product development through the integration of high-throughput experimentation (HTE), data science, and food processing
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to: Design, plan and conduct a programme of investigation, in consultation with the three supervisors. Produce a PhD thesis, written in English, consisting of four data chapters, an introduction and discussion
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developmental data and ecological validity. Infant data will be acquired in collaboration with Dr. Tessa Dekker (University College London) and Dr. Ingmar Visser at UvA. The project thus aims to quantify and
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if the necessary clean energy and energy infrastructure is available at competitive costs. Large-scale investments in the energy sector meanwhile get off the ground only if industry is prepared to electrify its