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Field
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Biological or Environmental Science or a relevant Masters qualification. You should have field experience and interest in avian ecology. Prior experience in spatial analysis is desirable. If your first
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Applicants should have a first or upper second class honours degree in Chemistry, Earth, Environmental, or Biological Science or a relevant Masters qualification. An aptitude for laboratory work and/or data
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Environmental Science or a relevant Masters qualification. You should have strong analytical skills, and interest in biodiversity, functional ecology, image/video analysis, and conservation. Experience with
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and implementing an embedded optimisation algorithm on representative hardware platforms to demonstrate feasibility and real-time performance. The primary application will be autonomous 6-DoF Moon
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work is linking microscopic (discrete) mechanics to macroscopic (continuum) models of active slender systems. The project involves three main components: Theoretical continuum modelling. Extend classical
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social value consistent with the mission of The Open University. You will work with subject specialists to develop an original contribution to knowledge as well as your skills in research, communication
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or another institution. Your proposed research must fall within one of the AHRC’s primary subject areas . We welcome interdisciplinary proposals but do be aware that at least 50% of your project must focus
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Nigeria (1900-present). Education, in a broad sense, applies to children and adults from various regions of Nigeria. Successful candidates may focus on any area of education, including primary, secondary
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relevant research experience, gained through Master's study or while working in a laboratory, are strongly encouraged to apply. How to apply Please apply via the University Applicant Portal. For further
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or programming is desirable. Eligibility Applicants should have a first or upper second class honours degree in geoscience discipline (essential) or a relevant Masters qualification, someone who can integrate data