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year of doctoral studies, the candidate will have the opportunity to acquire and develop digital research tools. Research questions may address concept annotation in small corpora, historical linguistics
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wide range of training courses, e-learnings, and educational programs—from professional specialization to personal development. This allows you to keep growing and make the most of your talents
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this goal, doped-diamond systems will be considered. The thermal stability of selected compounds under operating conditions will be assessed by means of molecular dynamics simulations with Machine Learning
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& Collaboration The successful candidate will work at the interface of machine learning and biostatistics, developing new theory, algorithms, and scalable implementations. By establishing a new class of multi-frame
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Gorlitz, Sachsen | Germany | about 1 month ago
Job description:Postdoctoral Researcher (f/m/d) in Machine Learning and Surrogate Modeling for Geochemical Systems With cutting-edge research in the fields of ENERGY, HEALTH and MATTER, around 1,500
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Description This doctoral position is part of GRAIL ("Gamma Radiation from the Atmosphere for Investigation and Learning"), a prestigious Horizon Europe Marie-Skłodowska-Curie Action Doctoral Network (MSCA-DN
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Description This doctoral position is part of GRAIL ("Gamma Radiation from the Atmosphere for Investigation and Learning"), a prestigious Horizon Europe Marie-Skłodowska-Curie Action Doctoral Network (MSCA-DN
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description Integreat - the Norwegian Centre for Knowledge-driven Machine Learning at the University of Oslo invites applications for a doctoral research fellowship. The PhD candidate will work at the
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approach based on Deep Learning algorithms will be developed and implemented to obtain additional information by coupling the recorded data. Furthermore, the increase in acquisition rates of measurement
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EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description PhD Position: Deep learning for phase-contrast synchrotron X-ray tomography Reference code: 2026