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thesis is not pre-defined and should be defined by the candidate over the course of the first year. The domain of the PhD thesis must be machine learning and either control theory, path planning, or multi
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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | 18 days ago
the communication and storage needed to retain most of the information. Environment. The PhD will take place at Inria Grenoble, in the Thoth team. This is a large team focused on machine learning, and
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Differential Imaging (CDI) to exploit the fundamental property of light coherence. The PhD will focus on two complementary approaches: 1) Enhancing CDI with machine learning: improve this technique using
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changes in sensory coding. We welcome applications from recent PhD graduates who are interested in these or related fields, particularly those who may bring a new technology or perspective to bear on
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Engineering » Electrical engineering Engineering » Control engineering Physics Mathematics Computer science Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 26 Apr
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Engineering, Science and Systems (DESS) research group focuses on data-intensive systems, spatio-temporal data management, data analytics, and applications of machine learning, with applications in digital energy and
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 3 hours ago
to constrain the representation of aerosols in the NASA GEOS Earth System Model. Activities that would be involved in this project include (but are not limited to): Implement machine learning transfer learning
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Website https://academicpositions.com/ad/tallinn-university-of-technology/2026/phd-posi… Requirements Research FieldArchitectureYears of Research Experience1 - 4 Research FieldEngineeringYears of Research
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engineering or similar. Knowledge and experience with deep learning models applied in computer vision. Remarkable academic trajectory, validated by a strong record of publications in relevant international
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MICADO (the first light instrument of the Extremely Large Telescope). The project provides a collaborative network, engaging with leading experts in optics, astrophysics, and machine learning from