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identification of safety liabilities. You will harness modern machine learning techniques to extract data from a range of relevant resources, such as clinical trials, publications and drug labels
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and database developers and work closely with the product team, machine learning engineers and data scientists to shape the next generation of literature discovery and AI-powered research services
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and database developers and work closely with the product team, machine learning engineers and data scientists to shape the next generation of literature discovery and AI-powered research services
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machine learning/AI with modern biology at the AI Hub Heidelberg as part of EMBL AI, a major institutional initiative to embed AI across all areas of life sciences. EMBL provides a unique environment for
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collaborative, proactive working style. You may also have A PhD in computer science, the life sciences, or a related field (not a requirement). Familiarity with AI/machine learning or computational
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Jira and Confluence; Experience with machine learning approaches, ideally in the context of data discovery. Contract length: 3 years (Project Limited Contract) Salary: Grade 5 or Grade 6 depending on
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for querying relational databases. Experience using AI-assisted coding and workflow tools to support reproducible data analysis, with appropriate human review Experience applying machine-learning
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with major life science resources, including PDBe, UniProt, PDBe-KB, and other relevant knowledge bases and databases Develop and deploy AI- and machine learning-based approaches for extracting
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EMBL sites and some international travel. You have An advanced university degree in computer science, machine learning, mathematics, computational biology, or a related discipline Ability to design
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AMBER, application and evaluation process etc please visit: ambercofund.eu. Your role Recent developments in cryo-EM workflows have highlighted how machine learning approaches can be successfully