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mathematics Engineering » Mechanical engineering Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 1 Apr 2026 - 12:00 (Europe/Paris) Country France Type of Contract
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experience in machine learning and molecular simulation ? We're looking for our future PhD student ! Join us at Université Côte d'Azur, recognized since 2016 for its scientific and educational excellence
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exciting opportunities for machine learning to address outstanding biological questions. The PhD student to be recruited will be working on the development of machine learning methods for single-cell data
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opportunities for machine learning to address outstanding biological questions. The PhD (M/F), to be recruited in the context of the ERC StG MULTI-viewCELL, will be working on the development of a new method
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2 Mar 2026 Job Information Organisation/Company Ecole Centrale de Lyon Research Field Chemistry Computer science Engineering Researcher Profile First Stage Researcher (R1) Positions PhD Positions
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● Completing a PhD Dissertation in Sociology at the Centre for Research on Social Inequality (CRIS), Sciences Po, Paris within the remit of the ERC LEARN project Where to apply Website https://www.sciencespo.fr
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Researcher (R1) Positions PhD Positions Application Deadline 30 Oct 2026 - 23:59 (Europe/Paris) Country France Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 1 Apr 2026
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(LIG), a 450-member laboratory with teaching faculty, full-time researchers, PhD students, administrative and technical staff. The mission of LIG is to contribute to the development of fundamental
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20 Feb 2026 Job Information Organisation/Company Centrale Supelec Department L2S Research Field Engineering » Communication engineering Researcher Profile First Stage Researcher (R1) Positions PhD
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 29 days ago
solving complex inverse problems that link measurements to their underlying causes. This PhD interdisciplinary programme focuses on Bayesian methods for estimating physical parameters from high-dimensional