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, the cores of the systems’ reasoning engines typically remain ‘symbolic’ (knowledge-based). These symbolic or neuro-symbolic software systems are of high practical complexity, which makes them difficult
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supervision with: Work and genetic engineer different cell lines. Set up diverse functional assays using innate immune cells and flow cytometry and microscopy readouts. Manage the labs’ tissue culture space
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