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) Positions PhD Positions Application Deadline 26 Apr 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 through the EU
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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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SAS), will be used. PhD candidate will acquire a broad range of experimental skills in materials diagnostics (e.g., X-ray diffraction, atomic force microscopy, Raman spectroscopy, and advanced
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; knowledge of or willingness to learn Dutch is a plus. You will receive close supervision, tailored training, and ample opportunities for personal and professional development within this PhD trajectory
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applying different multivariate calibration strategies and machine learning approaches. Finally, the variation of the sensor measurements will be studied in relation to the cow’s health and combined with
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) 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 through the EU
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HBIGS Heidelberg Biosciences International Graduate School | Mannheim, Baden W rttemberg | Germany | 9 days ago
Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 10 May 2026 - 23:55 (Europe/Berlin) Country Germany Type of Contract Temporary Job Status Full-time Hours Per Week 40 Offer
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Systems at The Technical Faculty of IT and Design invites applications for PhD stipends or integrated stipends in the field of Machine Learning for Intelligent Hearing Assistance in Complex Acoustic
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Job Offer from April 09, 2026 The International Max Planck Research School for Sustainable Metallurgy (IMPRS SusMet) offers PhD positions for three years for the following projects: Project 1
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) and define the problem mathematically. Secondly, a central component of the PhD will be to learn mappings between heterogeneous spaces through latent-variable models and representation learning. Some