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Field
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contributions in a team environment. Ability to work with minimal supervision, multi-task, and prioritize workload. Interest in mentoring junior team members. Interest in science communication (e.g., blog posts
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main purpose of the fellowship is research training leading to the successful completion of a PhD degree. For more information, please see our web site . Qualification requirements Applicants must
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& quantitative methods, with excellent academic writing, collaboration, organisation and communication skills. Desirable Criteria: Experience with transformer-based NLP models, web or social media engagement
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background in power systems, energy modelling, or grid optimisation Proficiency in GUI development (e.g. using Python Dash, Tkinter, or web-based frameworks) Experience working with data-driven simulation and
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print and web-based resources Present findings to supervisors and staff Agency and government relations 10% Respond to queries on science and technology policy Determine research needs and priorities
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; surveillance-data analysis; and scientific manuscript development for peer-reviewed publication. Gain experience with updates to DNPAO’s interactive, web-based data portal that displays Division surveillance
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& quantitative methods, with excellent academic writing, collaboration, organisation and communication skills. Desirable Criteria: Experience with transformer-based NLP models, web or social media engagement
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inclusion considerations at each stage of the research process section of the NSERC guide on integrating equity, diversity and inclusion considerations in research web page and the Guidelines
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collective agency. Disseminate research outcomes and participate in the public discourse through a variety of means e.g. opinion pieces, scholarly articles, conference papers, blog posts, etc. Qualifications
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Machine Learning Group, Department of Engineering, CambridgeMLG Cambridge About Us News Research Publications People PhD Admissions Blog Latest News Papers with MLG authors to appear at ICML and