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background with hands-on Python skills. Experience with predictive or uncertainty-aware modelling, AI-guided experimentation or related data-driven methods. Experience with materials, manufacturing
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machine learning/data science, with hands-on Python and experience with modern ML frameworks. Experience with one or more of time-series/sequence modelling, state estimation, constrained or Bayesian
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field by the appointment start date. Strong econometric theory, probability, statistics, and research skills in IV methods, causal inference, and machine learning. Proficiency in R, Python, MATLAB
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and analysis pipelines using MNE-Python, and contributing to the analysis of pilot EEG data. The post-holder will also support the development of behavioural coding approaches for social interaction and
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knowledge of deep learning, multimodal AI models, Vision-Language-Action models, or related technologies. Proficiency in Python programming and experience with deep learning frameworks such as PyTorch
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learning for materials discovery or quantitative image analysis, DFT calculations for catalyst design, experiences with MATLAB / Python / AutoCAD / COMSOL • Organic synthesis, polymer chemistry, synthesis
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• Excellent coding skills in python with pytorch (distributed deep reinforcement learning, Transformers, etc.) • Literature review/summarizing skills
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in triaxial testing and constitutive modelling Excellent programming skills, such as Python, MATLAB, or other competent languages. A good record of publications in reputable peer-reviewed journals
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machine learning methods • Proficiency in transport planning software such as EMME or PTV Visum. • Programming expertise in at least one language, e.g., Python, Java, or C++. • Strong written and
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) Experience working in Biosafety Level 2 laboratory Experience in computational data analysis, e.g., UNIX-based systems, R, Python, or similar tools for data processing and scripting Physical Requirements