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, artificial intelligence (AI), and socio-economic analysis. This program will equip them with advanced expertise in reservoir modelling, machine learning, advanced oxidation processes (AOP), and microbial
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physiology is an asset Experience in statistics and data analysis of large data sets (including time series analyses and machine learning) Good programming skills Very good communication and interpersonal
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development is important to us – we support you specifically and individually e.g., through training and networking opportunities specifically for doctoral candidates (JuDocS): https://go.fzj.de/JuDocs FAIR
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Leibniz-Institut für Analytische Wissenschaften - ISAS - e.V. | Dortmund, Nordrhein Westfalen | Germany | 29 days ago
regulations. Further information on data protection and the processing of personal data can be found at: https://www.isas.de/en/datenschutz . The closing date for applications is March 25, 2026. Please apply
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from research to application High ownership & steep learning curve Flexible entry: Internship (3–6 months) Full-time position Why Join Us? Most research stays in academia. At Cutaneon, your work will
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the Interdisciplinary Centre for Sustainable Development (IZNE). The doctoral students learn autonomous scientific work through participation in these international collaborative projects and centres. They also receive
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funding via an employment contract with the Max Planck Institute for the History of Science (MPIWG) or with Technische Universität Berlin and will have the possibility to teach. Two employment contracts
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Your Job: We are looking for a PhD student to contribute to the development of fast, accurate, and physics-informed machine learning models for predicting blood flow in patient-specific vascular
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and training provision within CAFE-BIO are available from the network website ( https://cafe-bio.org ) and the official EU page for the network ( https://cordis.europa.eu/project/id/101226762
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from the date of defense of your PhD and until September 9, 2026. Career breaks (parental leave, military service, work outside research, etc.) do not count towards the amount of research experience must