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environment affiliated with the European Laboratory for Learning and Intelligent Systems (ELLIS) Institute Finland. The selected candidate will contribute to the development and implementation of precision
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to work on the discovery of new superconducting materials with high critical temperatures, using novel methods and concepts such as machine learning and quantum geometry. The project is related to large
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(linking phenotypes, imaging, cytometry, or other readouts to transcriptomics) Statistics / machine learning for biological inference (model validation, differential state testing, embeddings/classifiers
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