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science and engineering. Access state-of-the-art laboratories and high-performance computing facilities. Gain experience by attending international conferences and training events. Develop skills highly
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environmental and regulatory pressures. High-value fruit crops remain especially vulnerable. Unlike arable systems, these crops rely on delicate, skilled manual handling within dense and variable canopies – tasks
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, machine learning, and photonics. Be part of a multidisciplinary research team spanning science and engineering. Access state-of-the-art laboratories and high-performance computing facilities. Gain
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, phase retrieval in this regime remains challenging, limiting multiscale imaging approaches in near-field holotomography. To address this, the PhD project combines machine learning, high-performance
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BeFC and Univ. Grenoble Alpes, CNRS, 38000 Grenoble, France | Grenoble, Rhone Alpes | France | 7 days ago
Dr. Andrew J. Gross) in the field of Biofuel Cells with a focus on electrochemistry and surface chemistry. The candidate will focus on the engineering of several concepts for novel high-performative
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Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description About the project
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transformations, providing sustained growth by way of fertilizer production. Notwithstanding, due to high functioning temperature and pressure, this 'simple' reaction accounts for greater than 1-2% of our annual
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Institut de Recherche pour le Développement (IRD) | Montpellier, Languedoc Roussillon | France | 7 days ago
Optional Skills / Knowledge Expertise in statistics Expertise in high-performance and parallel computing Expertise in neural networks Personal Qualities Intellectual curiosity Autonomy Adaptability Rigor
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applications. The project is partially funded by AMD, and the successful candidate will collaborate with AMD researchers. As part of this research, you will: Investigate how different AI tasks perform on AMD
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ponds of different types and ecological quality, by implementing an integrative approach using conventional, molecular and computational tools to generate a dataset that spans multiple trophic layers