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, data cleaning, econometric analysis and programming. QUALIFICATIONS Master’s degree in Economics. Ideally currently enrolled in a PhD program in Economics. SKILLS/KNOWLEDGE Scientific software: Advanced
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scientific articles for publication based on this data. Eligibility criteria PhD in Geological Sciences Selection process 1. PhD in Geological Sciences (4 points). 2. International mobility (maximum 1 point
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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | 27 days ago
. These simulations are run on highly parallel supercomputers on which both the hardware and the software are optimized for the task at hand. While the computing power of each processing unit is still increasing, the
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Engineering, Mechanical Engineering, Computer Science, Materials Science & Engineering, and Systems Engineering, and has interdisciplinary degree programs in Computer Engineering and Software Engineering
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software (e.g., Stata, R) Full details, see advert: https://www.strath.ac.uk/studywithus/postgraduateresearchphdopportunities/business/workemploymentorganisation
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improvement of the IMPRS program structures. Coordinate the full recruitment and admission process for PhD candidates. Act as a central communication point for students, faculty members, applicants, and partner
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articles, (e.g. for JSTOR Daily where we publish a Plant of the Month feature) and peer-reviewed articles. The fellow will also manage the editorial process for external submissions. Support and Development
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PhD fellowship (R1) to work on the MSCA project SAILING. The tasks to be carried out will be focused on developing a distributed energy optimization local controllers leading to the grid edge conceptual
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PhD fellowship (R1) to work on the MSCA project SAILING. The tasks to be carried out will be focused on developing a fault location and detection on the electrical and communication networks (including
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#:39540 Job Summary: How can we turn the vast and rapidly growing collections of publicly available biological data into reusable engines for discovery? And how do we build the software infrastructure