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Field
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research tasks and projects, making use of selected methodologies (longitudinal designs, moderation and mediation, causal inference), library research (Pubmed searches, systematic review methods), and
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methodologies (longitudinal designs, moderation and mediation, causal inference), library research (Pubmed searches, systemic review methods), and statistical analysis (data visualization, descriptive analyses
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Intelligence & Machine Learning Develop machine learning and AI models to identify, predict and characterise genome instability patterns. Design generative and predictive computational models to infer mutational
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methodologies (longitudinal designs, moderation and mediation, causal inference), library research (Pubmed searches, systemic review methods), and statistical analysis (data visualization, descriptive analyses
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text leveraging fine-tuned Vision-Language Models (VLMs) from WP3, supporting zero-shot reasoning and scene-graph inference. Ensure the system is deployment-ready by supporting benchmarking of inference
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inference pipelines suited to low-power wearable deployment, translating platform capabilities into demonstrable prototypes in collaboration with fabrication and electronics teams. Act as the technical bridge
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The Role: We are seeking an outstanding computational biologist to join the BioFAIR Pathfinder project to develop computational framework for gene regulatory network (GRN) inference methods in
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postdoctoral research associate to work with Professor Michael Desai at Harvard University on projects involving inferring sequence-function landscapes, using a combination of empirical data and ML methods (e.g
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inference? Join our team to study the causal effects of voting advice applications on political behaviour, leveraging a collaboration with the Norwegian Broadcasting Cooperation (NRK). Are you ready to take
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scene-graph inference. Ensure the system is deployment-ready by supporting benchmarking of inference speed, compute efficiency, and scalability with concurrent agents. Enable real-time adaptive learning