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teacher education. Using Teach for All as a case-study, the project aims to better understand how and why education polices travel across time and space. While policy mobility is driven by a wide range of
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such as surgery, patient or staff scheduling using, e.g., multi-objective optimization or machine learning approaches and analyzing efficiency-fairness trade offs. The research will be conducted under
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manipulation of fear and reward learning. This position is part of a recently funded, large-scale and innovative research program, aimed at creating new treatments for negative symptoms, among the most
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manipulation of fear and reward learning. This position is part of a recently funded, large-scale and innovative research program, aimed at creating new treatments for negative symptoms, among the most
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both independently and as part of an international, interdisciplinary team Assets•Experience with computer vision or deep learning (e.g. PyTorch, TensorFlow)•Familiarity with street view imagery or other
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. These methods will integrate machine learning techniques and real-time sensor data, to enhance operational efficiency, reduce costs, and ensure desired service levels, such as meeting a high percentage of demand
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machine learning You have good programming skills in Matlab, Python You have proven your proficiency in English language equivalent to B2 level You are enthusiastic and result oriented You can work
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are eager to learn new techniques or methods · You work independently and accurately · You have demonstrated verbal and written communication skills in English · You are
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to learn are essential. Solid programming skills in Python and/or R; experience with reproducible workflows (Git, Snakemake/Nextflow, containers) is a plus. Interest in cancer biology, tumor microenvironment
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Willingness to perform animal trials Strong written and spoken English communication skills These points are considered a plus: Being fluent in Dutch or willingness to learn Dutch First-hand lab experience