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structure in the results. The second is physics-informed learning, which combines available historical data with known system dynamics as a regulariser for data-driven learning — enabling nonlinear system
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to optimize performances. The postdoc will carry out structural and morphological characterizations (X-ray diffraction, TOF-SIMS, AFM, and microscopy) of the selected superconducting materials. In the second
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Advancement of large-scale shuttling based architecture with 2D-connectivity Migration to industrially fabricated devices
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 17 days ago
principles to the multi-objective setting and to developing new algorithmic strategies for efficiently exploring different regions of the Pareto front. A second assignment will concern the identification and
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to be held on the first or second week of December 2026
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are filled. The position is initially for one year, possibly extend to the second year depending on reasonable performance.
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and machine learning with density functional theory, or other similarly relevant computational methods, to advance understanding of materials design predictions for 2D and 3D systems with electronic and
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November 2nd, 2026. Internal candidates are preferred to apply before the 9th of October 2026. To apply, please send the following documents: complete and up-to-date curriculum vitae; motivation letter
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equipped with a range of sample environments, including a Langmuir trough and a reactor for chemical vapour deposition (CVD) growth of 2D materials on liquid metal catalysts (LMCat). Current in-house
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- $190,300/annually. Please note that the compensation for this Fellowship is approved as below: $90K – 1st year $95K – 2nd year JOB QUALIFICATIONS Qualifications The successful candidate must have: Ph.D. in