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to propose improvements in operational policies and storage capacities. To develop the project, The PhD student will be provided with adequate computer equipment and access to high-performance computing
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an advantage. The position is for three years, with an ideal start date between May 1 and September 1, 2025. The PhD project is focused on investigating spatial vision, appearance and redundancy
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20 Feb 2025 Job Information Organisation/Company IMT Atlantique Research Field Information science Technology Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country France
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The SiMul team (https://cran-simul.github.io) at the University of Lorraine is offering a fully funded PhD position on the theoretical foundations of self-supervised learning, focusing
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Mines Paris - PSL, Centre PERSEE | Sophia Antipolis, Provence Alpes Cote d Azur | France | 2 months ago
implementation in micro-computers. Methodology and expected results: The methodological focus is on the edge of machine learning and mathematical programming. The first step will be to carry out a bibliographic
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(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
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patient clusters and digital phenotypes, leveraging machine learning approaches to identify individuals at high CV risk based on clinical and biochemical markers, immune markers, digital health data (e.g
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Description of the offer : Spin triangles are magnetic molecules predicted to display spin chirality, magnetoelectricity and protected quantum degrees of freedom. These characteristics could allow electric spin control and long spin coherence properties. In the past we have confirmed the...
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behaviour using computational approaches such as Bayesian program synthesis and inverse reinforcement learning. Investigate the diversity of motor commands that could implement observed behaviours and explore
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Andries, SSL-Rehab: Assessment of physical rehabilitation exercises through self-supervised learning of 3D skeleton representations, Computer Vision and Image Understanding, 251, 2025, https://doi.org