483 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Mines Paris PSL" PhD positions in Germany
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data. Develop and apply machine learning models to estimate uncertainty in climate impact statements. Analyse spatial and temporal patterns and trends in climate-extreme impacts. Cross-validate
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-time full-time Programme duration 6 semesters Beginning Only for doctoral programmes: any time Application deadline Applications are possible throughout the year. For more information, please see: https
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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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opportunities specifically for doctoral candidates (JuDocS): https://go.fzj.de/JuDocs HEALTH & WELL-BEING: Your health is important to us. You can look forward to a comprehensive company health management
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month’s salary. All information about the TVöD-Bund collective agreement can be found on the BMI website (pay scale table on page 66 of the PDF download): https://go.fzj.de/bmi.tvoed PERSPECTIVE
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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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mentoring for building a career in academia or industry Professional development through JuDocS, including training courses, networking, and structured continuing education ( https://www.fz-juelich.de/en
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Additional information on beginning, duration and mode of study The starting date of the PhD project is flexible. The initial funding period is usually three years. Find out more at https://www.bgc-jena.mpg.de
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twin of sperm motility, and utilize it to develop a separation method. Your tasks will include: Performing computer simulations and matching them to experimental data Very close collaboration with
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embedded in the Bremen Research Cluster for Dynamics in Logistics (LogDynamics) (http://www.logdynamics.de ). LogDynamics is a cooperative network of research groups from five different departments