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(c) Application of the FETs in advanced HF electronics and biosensors for early diagnosis of AD/cancer. The proposed project is inherently interdisciplinary as it will integrate knowledge and
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representatives. The post-holder will have access to a range of data resources to inform the model, including blood donor cohorts from the COMPARE, INTERVAL and STRIDES studies. It is anticipated the work will
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schools for children…). For more information: https://cicenergigune.com/en/work-with-us Eligibility criteria CIC energiGUNE is committed to affirmative action, equal opportunity, and the diversity of its
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conducted. The thesis will benefit from all the necessary resources provided by the laboratory for conducting the project, including access to the PLASSMAT characterization platform at the IMN. It will be
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academic research training. It would suit candidates interested in careers in academia or industry, especially in AI, sensing, autonomy, robotics, or embedded systems. Background Accurate 3D mapping is
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of degree certificate in Spanish or English. If obtained outside the European Union it must be apostilled or legalised by the Spanish Embassy. 3. CV in English or Spanish/Galician 4. Responsible declaration
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to the South-East region of France. Hosted at Aix-Marseille University (AMU), it is designed as an interdisciplinary, intersectoral and international training initiative that will finance 20 PhD projects in 2026
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research, and a commitment to rigorous and reproducible science are essential. Previous applicants need not apply. How to Apply Prospective applicants are strongly encouraged to get in touch to discuss the
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 28 days ago
. They are therefore essential tools for software understanding, maintenance, and evolution, whether the software is new or legacy. The Moose platform has demonstrated its usefulness in industrial contexts, notably
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signals in the optical domain [2]. Photonics is set to became a major part of future AI systems, due to its inherently low energy consumption, high-speed data transfer and vast potential for parallelisation