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- PhD Programme "Gene Regulation in Evolution"
- NOVA.id.FCT- Associação para a Inovação de Desenvolvimento da FCT
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- ; The University of Edinburgh
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innovation processes and new products quickly, effectively, and efficiently, ensuring their quality and adequacy to customer needs. The main objective of this work plan is to implement the necessary tasks
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institution, developed in association or cooperation with one or more R&D units, a requirement to be duly proven at the time of signing the contract. Note: In the case of masters who are enrolled in non
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: Requirement 1: - To be a student enrolled in a master degree or integrated master or in an integrated master's program who has already completed the 180 credits corresponding to the first six curricular
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fully funded PhD position within the ERC-funded project “STAGE: From Stage to Data, the Digital Turn of Contemporary Performing Arts Historiography”, led by principal investigator Pr Clarisse Bardiot
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OF UNIVERSITY OF ÉVORA RESEARCH SCHOLARSHIP FOR MASTER - 1 VACANCY 10 of May of 2024 A call for tenders is open for one Research Scholarship for Master within the scope of the research project ERASMUS+ DEBSEUz
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credits at the official university master's degree level or equivalent. - Not to have a previous PhD degree. - Candidates who have been chosen for an interview with the Selection Committee, should bring
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to offer a fully funded PhD position within the ERC-funded project “STAGE: From Stage to Data, the Digital Turn of Contemporary Performing Arts Historiography”, led by principal investigator Pr Clarisse
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(HK-dir) whether the education (bachelor and master degree) in question is of a scope and level that corresponds to the level of a Norwegian master’s degree. Please see https://hkdir.no/en/ for more
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the world are invited to apply. All applicants must hold a Master Degree (or get it within the Starting date) or equivalent academic degree in the fields of Physics, Chemistry or Material Science. All
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Doughty: https://hazeldoughty.github.io/ Key responsibilities Conduct original and novel research in the field of Computer Vision, focusing on Video Understanding; Design and implement new deep-learning