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for international PhD candidates. What will you do? You will design, develop, and implement a series of interactive learning activities that support international PhD candidates before and after their arrival in
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 3 months ago
Biocatalysis and Green Chemistry to contribute to European Circular Bioeconomy, (1801P.01378.1.05 – Polymers-5B) financed by European Commission Workplan: The work plan of each grant is directly related to
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nephrology. What will you do? Design and optimise a transcutaneous vascular access port Develop and test biomaterials and surface coatings with a focus on hemocompatibility Perform in vitro experiments
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(PIDDAC) and the European Union's European Regional Development Fund (ERDF), through the programme. Work Plan: The fellow will develop research in the field of materials and devices for energy storage, with
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circuit behaviour, and active device characteristics. Prior exposure to power amplifier design, load-pull techniques, or nonlinear/behavioural modelling is considered an asset. Experience with RF/microwave
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program at the School of Biotechnology, in accordance with the theme and work plan of the grant to be carried out within the scope of the aforementioned project. Indeed, this doctoral program must be
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bachelor’s and master’s degrees in a field related to Biological Sciences, such as Biology, Genetics or Bioinformatics THE PROJECT: OikoLoss investigates how gene loss can drive evolutionary innovation. Using
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Framework Programme? Not funded by a EU programme Reference Number AE2026-0200 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 3 months ago
infrastructures such as IPFS (https://ipfs.io/ ) and Matrix (https://matrix.org/ ) on which we can plug replication mechanisms for file system synchronisation. Data replication algorithms have to be reliable (i.e
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the development of intelligent monitoring systems capable of detecting structural risks before failures occur. Work Plan Development of AI-driven models for Structural Health Monitoring (SHM). Final dissemination