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lab members, the group's organoid/tissue-engineered infection models (airway, gut) to prioritize physiologically relevant hits Co-supervise PhD students and contribute to method development, data
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by connectome-constrained artificial neural networks. Candidates from outside the field of neuroscience are encouraged to apply, but must be curious, persistent, and passionate to delve
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this new hybrid network. Your code will directly enable the next generation of energy-efficient AI clusters. Project scope You will bridge the gap between custom optical hardware and standard AI software
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special issues. Contribute to the supervision and the day-to-day scientific support of the PhD student working on WP1. Required profile Education and experience PhD in geography, urban planning, spatial
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combining experimental biology and computational genomics. Main duties and responsibilities Working and collaborating on research projects Analysis and publication of results Build a strong network in the
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to the technical and quantitative training of junior lab members. Candidate profile Applicants should have a PhD in biomedical engineering, electrical engineering, computer science, data science, computational