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PhD position: Global soil mapping with process-informed machine learning Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 36 to 40 Application deadline
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Job Description A PhD position in computational pharmaceutical science is available at the Department of Physics, Chemistry and Pharmacy (FKF) at the University of Southern Denmark (SDU). The
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this industrial PhD studentship in Physics – fully funded by the EPSRC and QinetiQ. We’re looking for a student who has a passion for science, with ambition to learn and apply their own ideas, perspectives, and
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20 Mar 2026 Job Information Organisation/Company Czech Technical University in Prague Research Field Physics » Other Researcher Profile Recognised Researcher (R2) Positions PhD Positions Application
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21 Mar 2026 Job Information Organisation/Company CNRS Department Institut de mécanique et d'ingénierie Research Field Engineering Physics » Acoustics Engineering » Materials engineering Researcher
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A large volume of data are routinely captured in high-performance training and competition environments. Whilst these data have the potential to inform key performance decisions, the full potential performance impact is often not realised. In some instances, this is because the volume of usable...
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scientists. This PhD studentship is the foundational computational element (WP1) proposed for a major 8-year project ("The Self-Driving Microscope”). The project’s goal is to build an autonomous, AI-piloted X
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Researcher (R1) Positions PhD Positions Application Deadline 20 May 2026 - 23:59 (Europe/Paris) Country France Type of Contract Temporary Job Status Full-time Offer Starting Date 1 Oct 2026 Is the job funded
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relevant to particle physics and cosmology. The candidate will use formal tools descended from string theory and supergravity, to perform analytical and numerical calculations of observable quantities in new
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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | 20 days ago
and machine learning. This project also takes place in the PEPR NumPEx, an initiative to improve the use of supercomputers for physical simulations. The results from the PhD will thus be integrated