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Field
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(fMRI), and eye-tracking measurements (main task) – Data analysis (main task) – Interpretation of results (main task) – Dissemination of findings through the writing of scientific articles (main task
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Robotics, Mechanical Engineering, Electrical Engineering, or a closely related field Proven research experience and publication track record in robotic manipulation, deformable object handling, or related
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methodology, theory, and applications across the areas of Bayesian experimental design, active learning, probabilistic deep learning, and related topics. The £1.23M project is funded by the UKRI Horizon
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presentation of analysis results. The ability to work with large and complex datasets. Excellent spoken and written English skills. Experience in machine learning, predictive modeling, and/or Bayesian methods
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closely related field Proven research experience and publication track record in robotic manipulation, deformable object handling, or related domains Hands-on experience with robotic hardware (e.g., robot
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to our work, meaning that we set up experiments in the lab or online to measure behavioural performance (e.g. response times and accuracy) to tasks involving object recognition and categorisation. Our
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human behavior. Preference will be given to candidates with 1) strong knowledge of Bayesian statistical and computational techniques; (2) prior track record of implementing and applying Bayesian
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Google Earth Engin, R, Python, and STAN (e.g., deep learning, Bayesian regression models, spatial analyses), and running analyses on a high-performance computing cluster. Demonstrated record of publishing
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projects ranging from score-based generative models, energy-based models, Bayesian analysis of graph and network structured data, highly multivariate stochastic processes; with data applications ranging from
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accelerators. The main objective of the postdoctoral project is the design, optimization, and implementation of compact focusing optics and beam diagnostics tailored to the specific characteristics of electron