185 evolution "https:" "https:" "https:" "https:" "https:" "Newcastle University" Fellowship scholarships
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Research (NCCR) AntiResist is a Swiss-wide research consortium funded by the Swiss National Science Foundation (SNSF). AntiResist is transforming antibiotic discovery and development through in vitro
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provide a critical step in the prevention of mental disorders. Where to apply Website https://pica.cineca.it Requirements Additional Information Eligibility criteria Eligible destination country/ies
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of January 2026 WHO WE ARE INESC-ID (www.inesc-id.pt ) , “Instituto de Engenharia de Sistemas e Computadores: Investigação e Desenvolvimento em Lisboa” is a Research and Development and Innovation Organization
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English as the primary language. Career development support and mentoring throughout the program. Interdisciplinary coursework and research opportunities across different areas of science, engineering and
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(www.inesc-id.pt , “Instituto de Engenharia de Sistemas e Computadores: Investigação e Desenvolvimento em Lisboa” is a Research and Development and Innovation Organization (R&D+i) in the fields
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testing during different production stages of edible insects - Impact of tested products on the human gut microbiome Applicable legislation and regulations: Statute of the Scientific Research Fellow: https
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 1 month ago
national funds through FCT and co-financed by the European Regional Development Fund (FEDER) through COMPETE – “Programa Operacional Fatores de Competitividade Workplan: The work to be developed will focus
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 24 days ago
the submission of the following documents: i) B1 Form – Fellowship application (http://drh.tecnico.ulisboa.pt/bolseiros/formularios/ ); ii) Curriculum Vitae; iii) academic degree certificate, where applicable; iv
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reference. The student will focus primarily on the photonic integration of machine learning methods, contributing equally to the development of ML algorithms in this context. Their work will include
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efficiency, demand-side management, and sustainable urban development through advanced modelling and optimisation approaches. It will also explore the role of smart building control strategies and the