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for improving the environmental impacts of wood production over broad spatial scales. Required Skills and Qualifications: PhD in a forestry- or conservation-related discipline. Strong background in field survey
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on and defensive mechanisms for safe multi-agent systems, powered by LLM and VLM models. Candidates should possess a PhD (or be near completion) in Machine Learning or a highly related discispline. You
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successful candidate will have a PhD (or equivalent) in the field of space physics or a closely related area. They will have the skills and abilities to conduct high-quality innovative research and to
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involves high level of collaboration with both the QMUL Space Plasma Group and the QMUL Detector Development Group. About You The successful candidate will have a PhD (or equivalent experience) in the field
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research. The post is funded for four years as part of a four-year project grant from The Leverhulme Trust. You will have a PhD (awarded or soon to be awarded) in comparative vertebrate anatomy and/or
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and experience: Essential criteria PhD in Neuroscience Experience in rodent stereotaxic surgeries. Experience in Electrophysiology recordings in vivo in rodents Experience in Electrophysiological signal
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. About you: To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria PhD in Neuroscience Experience in rodent stereotaxic surgeries
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ambitions We are seeking a candidate with: Educational background PhD in Architecture, Landscape Architecture, Computational Design, Computer Science, Urbanism, or a closely related field. Specialization in
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to communicate effectively with key stakeholders are essential. You will have a PhD (or will be close to submitting/defending your thesis) in experimental nuclear or particle physics or in a discipline relevant
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this role, we are looking for candidates to have the following skills & experience: Essential criteria PhD, or in the final stages of obtaining a PhD, in a relevant area of social science (e.g., sociology