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Please apply here: https://apply.workable.com/ellison-institute-of-technology/j/91F1A5719B/apply/ Led by a world-class faculty of scientists, technologists, policy makers, economists and
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chemistry or chemical engineering, a strong publication record, a pro-active approach and strong expertise in gas phase heterogeneous catalyst testing and in catalyst synthesis and characterisation. The post
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Postdoctoral Researcher in ML for Dynamical Systems Representation, Prediction, and State-estimation
initiatives within the Aalto House of AI. Your experience You have a recent doctoral degree in electrical engineering, control engineering, computer science, applied mathematics or a related field. Programming
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the benefit of humanity. GBI is part of the Ellison Institute of Technology, Oxford (EIT) and is led by founding Director Jason Chin. The vision of the Generative Biology Institute is to lay the foundations
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2025). Our microchip-based escape-time technology platform now enables measurements of the physical properties of macromolecules such as their electrical charge, size and 3D conformation with
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, with a theoretical energy up to ten times that of current lithium-ion cells. This role is part of an exciting project that brings together scientists and engineers to tackle the key challenges preventing
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and optimisation but not limited to data driven monitoring for control and operation. You must have a good master’s degree in electrical engineering, with Power and Control Engineering major
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technical issues. Broad understanding of current developments in relevant fields and the ability to identify promising directions for future research and technology development. Innovative thinking with a
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technology are particularly desirable for the role. Candidates with a record in interdisciplinary research at the cross-section of technology and security/policy will also be highly desirable for the role
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, Statistics, Electrical Engineering, Computer Science, or a related field. Key Criteria Demonstrated experience with mathematical modelling, algorithm design, or theoretical analysis of learning systems