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the required criteria 8. EVALUATION Composition of the Assessment Committee: - Presidente: Prof. Dr. Sofia Cerasoli Salvatori, -effective panel members: Dr. Silvia Catarina Peixeira Carvalho, Dr. Susete Maria
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Faculdade de Ciências Médicas|NOVA Medical School da Universidade NOVA de Lisboa. | Portugal | about 2 months ago
supervision of Prof. Doctor Sandra Tenreiro, as well as other locations necessary for the preparation and implementation of the project activities. Duration and start date The fellowship will have an initial
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), under the guidance of Prof. Victor de Freitas, Prof. Susana Soares and Dr. Joana Oliveira. Grant duration: Initial duration of 8 months, with beginning on 1 November 2025, eventually renewable up, but not
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the contractual phase of the scholarship. The applications must be sent to Prof. Joana Amaral Paulo via email: forchange@isa.ulisboa.pt . The application period will run from November 4th to 17th, 2025. 4
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will be developed in the Department of Chemistry and Biochemistry, Faculty of Sciences of the University of Porto (FCUP), under the guidance of Prof. Victor de Freitas, Prof. Susana Soares and Dr. Joana
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Street Rua Prof. Anibal Bettencourt, n.º 9 Postal Code 1600-189 E-Mail recrutamentos@ics.ulisboa.pt STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More share options E-mail Pocket Viadeo
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Information Work Location(s) Number of offers available1Company/InstituteFMUP - Faculdade de Medicina da Universidade do PortoCountryPortugalCityPortoStreetAlameda Prof. Hernâni Monteiro, 4200-319 Porto
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Telecomunicações at Aveiro, under the supervision of Prof. Telmo Reis Cunha. Duration: 6 months, with the possibility of renewal. This type of scholarship has a maximum duration of 1 year. Start date: October 2025
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to be achieved: Development of algorithms for analyzing facial expressions in static and video images. Analysis and evaluation of identity bias in facial expression recognition. V - Initial grant duration
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until the time of signing the contract. Activity Outline: Grant holders will work on the following topics TASK 3: Empirical Analysis of Deep Learning and Generative Modeling Algorithms TASK 4: Development