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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | about 20 hours ago
Engineering ii. Basic knowledge of Python iii. Basic CAD modeling skills acquired during academic training iv. Introductory familiarity with numerical simulation (e.g., finite element method and meshless
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-determination. In-depth consultation with community leaders, health experts, and other local knowledge carriers—and circulation of lessons learned through routine academic publication and community dissemination
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Nadia Mihaychuk Postdoctoral Fellowship in Ukrainian Studies is awarded to promising junior scholars to support research that advances knowledge of Ukraine. This fellowship is designed to bring early
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and responsible space exploration, with planetary protection at the core of its efforts. You are encouraged to visit the ESA website: https://www.esa.int/ Field(s) of activity/research
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research activities. Solid theoretical and practical knowledge in molecular biotechnology techniques (such as gene cloning and recombinant protein production). Knowledge on DNA, RNA and protein extraction
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for Responsible AI – Refª C628696807-00454142 funded by Recovery and Resilience Plan (RRP) https://recuperarportugal.gov.pt/ and Next Generation EU European Funds Application submission from 26-Feb to 12-March
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-in-machine-learning-for-cognitive-neuroscience Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/294553/phd-research-fellow-in-ma… Requirements Research FieldComputer
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application end stations to be used for imaging, absorption/reflection spectroscopy, and other quantum sensing techniques. Practical working knowledge and hands‑on experience with lasers and optics, spanning
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. Whilst prior knowledge of the lymphatic system is not essential, a good understanding of disease genetics will be highly valuable. Strong organisational, time-management and communication skills
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Is the Job related to staff position within a Research Infrastructure? No Offer Description Integreat – the Norwegian Centre for Knowledge-driven Machine Learning at the University of Oslo invites