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of the Saez Rodriguez group is to acquire a functional understanding of the deregulation of signalling networks in disease and to apply this knowledge to develop novel therapeutics. We focus on cancer, auto
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environments such as slurm; Experience with bioinformatic pipeline libraries such as nextflow; Peer reviewed papers in RNA biology; Experience with LLMs and other machine learning methodologies; Experience with
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greatest challenges. Please watch the video below to learn more about EMBL and how our work makes a difference. Whatever your role, you will be contributing towards these challenges. Campus life & benefits
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The Machine Learning for Health team in the Data Science and Genetic Epidemiology Lab at the Institute for Molecular Medicine Finland (FIMM) , University of Helsinki, is currently seeking a highly
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within a Research Infrastructure? No Offer Description The Machine Learning for Health team in the Data Science and Genetic Epidemiology Lab at the Institute for Molecular Medicine Finland (FIMM
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using hybrid models combining mechanistic, GenAI, and machine learning approaches. You’ll contribute to building disease-specific Digital Twins using large-scale single-cell multi-omics datasets
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. Computer skills. Able to communicate in English in a professional environment. Contract length: 1 year Salary: Grade 3 Why join us EMBL is curiosity-driven, community-oriented and international. As an
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is connected to the vibrant local ecosystem for data science, machine learning and computational biology in Heidelberg (including ELLIS Life Heidelberg and the AI Health Innovation Cluster ). Your
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, and Bash Excellent communication skills You might also have Familiarity with modern machine learning, in particular large language models Experience with the design and implementation of web interfaces
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causal modelling. Provide methodological and analytical support to projects aimed at personalised and predictive medicine. Application of artificial intelligence: Provide support in AI and machine learning