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Field
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professional development and work with the technology transfer office to identify potential inventions and understand IP processes. Collaborate in preclinical and translational research projects involving murine
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tasks include: AI support in the process chain: developing and applying image analysis, data process analysis, and sensor technology for textile production; using machine learning for process optimisation
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structural data. Develop workflows for time-resolved crystallography data processing. Integrate molecular dynamics with AI/ML methods. Benchmark protein foundation model performance and integrate them with
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-based reasoning strategies for oncology, including tool-augmented inference, multi-agent or compound model workflows, process supervision, verifier-guided training, and reinforcement learning-based post
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division "Catalytic Interfaces for Chemical Hydrogen Storage" (IHE-1), led by Prof. Dr. Hans-Georg Steinrück, we investigate mechanisms and processes in (electro)chemical energy storage systems
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the platform by embedding/developing additional tools for data processing and analysis. The starting point for the developments will be our EasyNMR platform (see easynmr.pastis.dk ). Current application areas
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Materials, Electronics and Communications) and eight Research Nodes which group staff under technical expertise and interest (see https://www.durham.ac.uk/departments/academic/engineering/research/ ). We
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knowledge in systems and/or cognitive neuroscience Knowledge of brain imaging analysis methods Knowledge of multivariate statistics and/or digital signal processing Fluency with the Unix operating system and
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of materials and devices during switching, combining methods such as laser pump and X ray probe total scattering, WAXS and SAXS, imaging, and femtosecond X ray diffraction to probe structure and dynamics in real
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Familiarity with brain imaging analysis acquisition Knowledge of multivariate statistics and/or digital signal processing Proficiency in Python. Parallel computing processing experience is highly appreciated