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with clinical populations or translational research settings. Strong programming skills (e.g. Python, MATLAB, R) and experience with statistical modelling or machine learning. A strong publication record
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Vacancies Postdoc position on Federated/Continual Learning for Time-Series IoT Data (TRUMAN Project) Key takeaways In this role, you will address the intricate challenge of enabling AI to learn
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outcomes under different market design scenarios. The research will combine machine learning, stochastic optimization, and agent-based modelling with behavioural experiments. Case studies from emerging
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and digitizing archival data, strong knowledge of causal inference methods, good command of R and Python. Knowledge of machine learning methods is an asset. Strong command of English; command of either
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, including abstract geospatial workflows; design AI- and machine-learning-based methods that automatically describe and model geodata sources using textual metadata (NLP) and the geodata itself; contribute
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cases. We are particularly interested in how AI, Data Science, or Machine Learning techniques can be used to quantify and assess software and system security from open source software to cloud services
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populations or translational research settings. Strong programming skills (e.g. Python, MATLAB, R) and experience with statistical modelling or machine learning. A strong publication record and excellent
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transport proteins in lipid membranes. Furthermore, the ultimate long-term goal is to integrate these cells in a dialysis machines. The objectives for this position are to: Formulate synthetic cells with
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layers across heterogeneous platforms. Ideally you would have familiarity with deploying or supporting AI and machine-learning workflows, including large models, large network analytics, or multimodal data
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, testing and modelling techniques under ESA’s research and technology programmes; applying EMC analysis and modelling tools and evaluating the results obtained; monitoring applicable scientific and