96 software-engineering-model-driven-engineering-phd-position Postdoctoral positions in Netherlands
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position offers an exciting opportunity to work at the intersection of bioinformatics, mass spectrometry, and AI-driven cancer research. You will be part of a dynamic, multidisciplinary team specializing in
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://www.rug.nl/(...)itions-of-employment ): A salary of € 4,020 gross per month (salary scale 10.4) based on a full-time position (1.0 FTE), depending of relevant work experience after attaining a PhD. A gross
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external link , as well as discounts on software and other IT products. We also offer access to additional employee benefits through our Terms of Employment Options Model. In this way, we encourage our
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group at the Groningen Research Institute of Pharmacy (GRIP). This two-year position offers an exciting opportunity to work at the intersection of bioinformatics, mass spectrometry, and AI-driven cancer
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on their expertise and tasks, fostering their professional development. RIDE supports self-reflection across five key domains of the university’s Teacher Development Model (more information: Our vision on teacher
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or several applications related to requirement engineering, system and subsystems design, modelling, implementation, analyses, verification, testing, validation and qualification. Typical areas where the use
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for this position will have the following qualifications/qualities A PhD degree in either machine learning or computational molecular sciences. Advanced knowledge in molecular machine learning. Advanced knowledge in
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looking for a postdoctoral researcher with a background in electrochemistry. The candidate should have completed a PhD in electrochemistry, ideally with experience in electrochemical sensing. The candidate
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technology, have the potential to revolutionize consumer-goods and products. ARC CBBC has a strong focus on sustainability, enabling transitions towards a circular and more balanced economy with regard
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in combination with other machine learning techniques, to create predictive models. You will engage in an interactive feedback loop with domain experts to analyze discovered models and remove any