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is available at https://colalab.ai/ . At EI, the group will develop an ambitious Generative Digital Biology (GDB) programme, developing multimodal, cross-organism and experimentally grounded AI systems
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. The post offers extensive collaboration across the Institute, supporting AI-guided design-build-test-learn workflows, biological discovery, and the development of open algorithms, benchmarks, and
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mechanics, machine learning or applied/computational mathematics. ● Demonstrated ability to carry out original mathematical derivations and/or develop computational tools, evidenced by publications
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modeling and AI. This position will include: Developing new Generative AI algorithms for developing intelligent agents in areas such as planning, exploration, perception, physical reasoning, and memory
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the cellular and molecular pathways disrupted in brain disorders such as schizophrenia and autism, by utilizing recent advances in genetics and genomics. We are developing and applying tools to understand how
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for tumor behavior and clinical outcomes Development and implementation of artificial intelligence and machine learning algorithms for biologically and clinically motivated questions in pediatric oncology
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to evolutionary time scales. One of the goals of the SCINet Initiative is to develop and apply new technologies, including AI and machine learning (ML), to help solve complex agricultural problems that also depend
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and porting of scalable science applications and algorithms for OLCF and other leadership computers. Debugging and tuning applications for high performance. Developing performance models of existing
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A postdoctoral research associate is sought to develop an experimental (hardware) platform that enables efficient exploration of complex parameter spaces. The platform will integrate comprehensive
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on developing deep learning methods for the reconstruction and physical analysis of ATLAS experiment data. The selected candidate will develop innovative analysis methods for the reconstruction and physical