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biology and bioinformatics, as well as in Machine Learning (including Large Language Models). Good understanding of evolutionary and molecular biology concepts, and good statistical (data analysis) and
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Your Job: The conventional, manual co-design of algorithms and hardware is slow and inefficient. Our group develops methods and tools to automate the co-design process. The core of this project is
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combines computational analysis, evolutionary experiments and genomics, to gain a deep insight into how cancers adapt. Research projects in the Cresswell group are supported by the Austrian Science Fund (FWF
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combines computational analysis, evolutionary experiments and genomics, to gain a deep insight into how cancers adapt. Research projects in the Cresswell group are supported by the Austrian Science Fund (FWF
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in a broad and impartial manner. The work can draw on algorithms from the recent work of the process design management team. Several generative algorithms have been produced: using evolutionary
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understanding of gene presence/absence, structural variations, and evolutionary dynamics. In this project we will aim to develop novel dynamic programming computational methods for pangenome assembly of diploid
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molecular biology techniques as well as in algorithms, statistics and artificial intelligence for molecular genetics. Importantly, mastery of the experimental and theoretical aspects shall equip doctoral