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Field
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. The successful candidate will design and execute robot-driven experiments and will analyze the resulting spatial data, closing the loop between experimental design, automated execution and data-driven decisions
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they promote translocation biogenesis, and testing them in preclinical models. The work combines CRISPR engineering of B cells, protein biochemistry and genomics approaches including RT measurements, replication
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the Peng Research Group . The successful candidate will conduct research at the intersection of scientific AI, atomistic simulation, computational catalysis, and data-driven materials discovery. The position
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CGIAR, including CIMMYT and National Agricultural Research Systems (NARES). In this role, you will develop an analytical decision-support tool that integrates quantitative genetic modelling, artificial
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large-scale genomic, phenotypic, environmental, and field trial datasets, you will benchmark AI and quantitative genetics methods, develop multimodal and hybrid modelling frameworks, and investigate
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concepts from nonlinear system identification, optimisation, computational complexity, and data-driven modelling, with the long-term objective of extending these ideas to modern AI and machine learning
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network or computational modeling. The ideal candidate will have a strong interest in applying these tools to theory-driven questions of group formation and intergroup relations, but we are also open to
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intelligence-driven approaches to industry challenges, such as warehouse management, ocean freight optimization, and reshoring high-technology industry sectors such as semiconductors and electric vehicles
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About the Role Applications are invited to join an ERC-funded research programme. The successful candidate will work at the interface of bioelectronics, mechanobiology, and disease modelling
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interactions and treatment of apicomplexan parasites, including Cryptosporidium and Toxoplasma gondii. What we offer • A 24-month fully funded postdoctoral position ; • a discovery-driven research project