1,302 computer-programmer-"https:"-"Inserm"-"UCL"-"FEMTO-ST"-"https:"-"https:" PhD positions
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Zürich. The candidate will work on the Empa Campus in Dübendorf and will be enrolled in the doctoral program of ETH Zürich. The position is available from 1st July 2026 (or later upon agreement). We live a
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Applicants are invited for a PhD fellowship/scholarship at Graduate School of Technical Sciences, Aarhus University, Denmark, within the Ecoscience programme. The position is available from 01
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The UKRI-funded 5-year project, 'Colombo: Layered Histories in the Global South City', selected for funding by the European Research Council under its 'HORIZON' programme, is recruiting to a
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. The group consists of doctoral and post-doctoral researchers from diverse backgrounds. For more information, please visit our website: https://wwwen.uni.lu/snt/research/finatrax/projects Successful candidate
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program in partnership with Banner – University Medical Group (B-UMG). Clinical activities will be at Banner MD Anderson Cancer Center, which has an established and growing dermatology program specializing
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engineering, building physics, material science, data science, or a related field. Foreign degrees must correspond with the admission criteria for the PhD program. Candidates submitting M.Sc. thesis within 30
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double) PhD program between Ghent University and their home university. Students selected under this preference program will be exempted from paying tuition, bench fees, or any other study-related costs
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UiA-CERN PhD Position in Multi-robot Mapping and Environmental Data Sharing - Uncertain Environments
UiA. The successful candidate will spend 18 months at UiA followed by 18 months at the BE-CEM group at CERN, while remaining active in the PhD programme at UiA for the full 36 months. The PhD Candidate
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the wind/renewable energy training and research elements of the CDT programme. Funded by Statkraft and EPSRC, this 4 year this PhD studentship, at the University of Strathclyde is in the area of data
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with NEOM, one of the world’s largest ecological restoration programmes, the project will develop machine-learning approaches to analyse satellite observations of vegetation change and evaluate large