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. The research group is seeking a talented Doctoral Researcher in nonlinear systems and control with strong interest in nonlinear stability theory, modeling & identification, optimal control, certifiably safe
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proficiency in relevant programming languages (e.g., Python, C++) and tools such as ROS. Experience in simulation and digital twins, as well as the use of synthetic data for training machine learning models, is
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computational mechanics of composite materials, and should be enthusiastic to work in a collaborative project between industry and academia.Vacancy 3: PhD (4 years) or postdoc (3 years) on mechanical modelling
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to produce resilient and high-performing models. · PhD in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field Strong track record of applying ML in academic or industry
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received after the review date will only be considered if the position has not yet been filled. Position description The Computational Medicine Research Group led by Prof. Pratik Shah at the University
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Max Planck Institute for Demographic Research (MPIDR) | Rostock, Mecklenburg Vorpommern | Germany | about 1 month ago
for highly-motivated and qualified candidates to work with an international team on developing cutting-edge novel demographic, statistical and computational methods in estimating, modelling and forecasting
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The Biomedical Image Analysis Group, led by Prof Ben Glocker, in the Department of Computing at Imperial College London is seeking a talented Research Assistant / Associate to take a key role in an
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Application Deadline 12 Sep 2025 - 23:59 (Europe/Lisbon) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job
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dynamics and tissue morphogenesis during embryo development using cellular, molecular and mechanical approaches. Cell movements underlie tissue patterns and shapes. Using chick embryos as the model system
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We are seeking immediate post-doctoral positions in Alzheimer’s disease and related neurodegenerative diseases, by developing quantitative methods on transcriptomics datasets from stem cell models