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(DDLS) use data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and global
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ARDITI - Agência Regional para o Desenvolvimento da Investigação Tecnologia e Inovação | Portugal | 2 months ago
. ARDITI – Regional Agency for the Development of Research, Technology and Innovation – Association will act as the data controller (as defined in the GDPR), with the collection and processing
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is mandatory for contract signature. More information can be obtained in: https://www.dges.gov.pt/en/pagina/degree-and-diploma-recognition . II. Preferential Requirements Experience in working with GIS
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17 Jul 2026 Job Information Organisation/Company Wageningen University & Research Research Field Engineering » Water resources engineering Environmental science » Water science Researcher Profile
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 3 months ago
at the junction of applied mathematics, robotics and computer science A sensibility to and interest in the designing robot more adapted to humans The will to learn the job of a researcher A critical but positive
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A fully funded Geography PhD exploring how people, families and places navigate the shift from nuclear operations to decommissioning. The University of Exeter’s Department of Geography is inviting
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the Network and receive the support of other network leads and opportunities to collaborate with industry partners. More information about the project and its aims: https://www.sum4products.co.uk/about What you
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options for traveling. The employment duration is 4 years. Initially limited to 1.5 years, the employment relationship is automatically extended to 4 years if the employer does not terminate it within
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Join ABC Labs and KTH as an Industrial PhD Student to build data-driven models of human biology with multimodal health data — interdisciplinary impact, real-world healthcare. About the role We
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-world environments inevitably face noisy data, distribution shifts, and situations their training never anticipated. Existing machine learning research focuses on limiting the impact of such disturbances