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algorithms to guarantee the reliable operation of semiconductor machines, together with a highly innovative industrial partner in the Brainport region. If all these sounds fascinating, then this PhD position
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PhD: Building the infrastructure for (mass) mobilisation Faculty: Faculty of Geosciences Department: Department of Sustainable Development Hours per week: 36 to 40 Application deadline: 15
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Wetsus - European centre of excellence for sustainable water technology | Netherlands | about 2 months ago
Technology » Environmental technology Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 6 Apr 2026 - 15:00 (Europe/Amsterdam) Country Netherlands Type of Contract
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PhD Money in postdivorce families: Resource pooling and transfers to children Faculty: Faculty of Social and Behavioural Sciences Department: Social Sciences Hours per week: 36 to 40 Application
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Listen Published Monday 23 Mar 2026 Deadline Thursday 7 May 2026 Work area PhD Organisational unit Erasmus School of History, Culture and Communication (ESHCC) Salary € 3.059 - € 3.881 Employment
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support the failing heart—at the exact moment it matters most? This PhD position bridges a state-of-the-art Mechanical Circulatory Support (MCS) experimental lab with real-world clinical analysis in
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lives? If so, please continue reading! Join Us! The Computational Science Lab is looking for an ambitious PhD candidate to bridge the gap between computational modeling and experimental biomedicine. You
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? No Offer Description Are you interested in how creative practices and competencies foster better collaboration between citizen collectives and local governments? Apply for this PhD position and join
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analysis is crucial to evaluating the cost-effectiveness of psychosocial and tech-based support to improve the lives of people with dementia and their informal caregivers. PhD Candidate in Health-Economic
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-physical systems secure and resilient in the presence of uncertainty and cyber-physical attacks? Then you may be our next PhD candidate in resilient and learning-based control of cyber-physical systems