67 programming-"Multiple"-"NTNU---Norwegian-University-of-Science-and-Technology" positions in Netherlands
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. We aim to unravel cell signaling programs that underlie adverse xenobiotic-induced adverse responses that drive pathological outcomes. A focus is on critical target organs of toxicity, e.g. liver
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are encouraged to submit a research proposal that aligns with UCALL's research programme and encompasses multiple areas of law. Your job Over a period of four years, you will conduct a PhD research under the
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to sustainable and inclusive transport? How can private, shared and public transport be integrated in mobility hubs? How to combine data and share data across multiple partners involved in developing smart
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to collectively explore urban futures? This position is hosted by the Faculty of Geo-Information Sciences and Earth Observation (ITC) within the Sector Plan Beta II program’s focus area on Spatial Dynamics, which
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to work at multiple laboratory locations. A good command of both Dutch and English. A customer- and service-oriented mindset. In our international working environment there is an increasing amount
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challenges. You are comfortable working in environments with multiple stakeholders and diverse interests. You enjoy diving into complex systems and love solving puzzles. You’re good at setting priorities and
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similar field; expertise in programming skills and statistical data analyses, including machine learning; affinity with environmental exposure modelling and high-performance computing; strong reporting and
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interest in environmental health and Exposome research; expertise in programming and quantitative data analysis, including machine learning in R/Python; affinity with bioinformatics; strong collaboration
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combine multiple techniques, picking those that complement each other. In particular the use of non-destructive techniques is important, avoiding unintentional sample modifications. Although such “hybrid
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). This includes identifying new factors that drive disease progression. The primary focus will be on using state-of-the-art genetic programming (in particular: GP-GOMEA) for small, explainable expression discovery