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sequencing and synthesis to design useful cell behaviors. The scope of this project is to combine multi-gene control technology and computer algorithms to develop a foundational discovery platform for future
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different aspects of evolvability – the ability of organisms to evolve. We are interested in developing computational and mathematical tools to understand and quantify evolvability while exploring its
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environment project, we will develop automated species and community recognition, particularly focusing on pathogenic soil fungi, with help of deep-learning algorithms fed with microscopic image and Raman
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in their computation. We want to understand the fundamental principles that permit us to build privacy-aware AI systems, and develop algorithms for this purpose. The group collaborates with several
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of Computing Science has been growing rapidly in recent years, with a focus on creating an inclusive and bottom-up driven research environment. Our workplace consists of a diverse set of people from different
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application! We are now looking for Computational Research Assistants in Tumour Evolution and Single-cell Genomics. The position Cancer evolves over time and space, with subclones often acquiring new mutations
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intended support design decisions related to manufacturing and process parameter selections; known to influence the material microstructure. Duties: The post doc will develop and apply computational methods