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and other data-driven use cases across VIB. Working directly with data, pipelines, transformations, models and code, you build and implement robust and scalable data solutions as part of your day-to-day
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data-driven use cases across VIB. Working directly with data, pipelines, transformations, models and code, you build and implement robust and scalable data solutions as part of your day-to-day work. The
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management and communication skills, with the ability to navigate different interests and perspectives. Excellent command of English and Dutch, both written and spoken. Our offer A full-time, open-ended
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computational approaches – including structural modelling, cheminformatics, and AI-driven methods – as part of the broader toolkit to enable program decisions, integrating computational predictions with rigorous
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mathematical models to address fundamental questions in biology. Examples of research topics include but are not limited to: development of new AI architectures for biology and hybrid models that combine deep
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Group Leader and Professor AI in Biology - Dept of Computer Science and Dept. Electrical Engineering
interested in recruiting faculty members who use and develop artificial intelligence methods and mechanistic mathematical models to address fundamental questions in biology. Examples of research topics include
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independently execute routine workflows, such as DNA/RNA quality control, library preparation procedures, setting up sequencing runs on our NGS instruments etc. Besides manual execution of some laboratory
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get energy from supporting colleagues, you are passionate about science and enthusiastic to be part of a dynamic research lab. Strong communication and interpersonal skills Good command
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. Ideally, the candidate will develop and/or make use of innovative reductionist (i.e. 3D tumoroid models) or in vivo models (i.e. mouse genetics, in vivo lineage tracing, PDXs,…) and establish clinical
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, the candidate will develop innovative reductionist (i.e. 3D tumoroid models) approaches and unique in vivo models (i.e. mouse genetics, in vivo lineage tracing, PDXs,…) to gain novel mechanistic insights and