19 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" positions at Faculdade de Ciências e Tecnologia in Portugal
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on the Caparica Campus, in the Department of Life Sciences, UCIBIO – Unit of Applied Biomolecular Sciences, Glycoimmunology Group-https://glycoimmunology.webhost.fct.unl.pt , under the scientific supervision
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. 6. Workplace The work will be carried out at the Department of Electrical and Computer Engineering of the NOVA School of Science and Technology of NOVA University Lisbon, under the scientific
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the relevant application form, which is available at http://www.fct.unl.pt/faculdade/concursos/docentes , where the candidate must state their consent to communications and notifications related
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stage. 3. Preferential Factors Proven experience with decision support systems based on knowledge bases and machine learning. Previous experience in machine learning applied to dynamic systems or orbital
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to provide the supporting documents by the grant contracting stage. 3. Preferential Factors Proven experience with decision support systems based on knowledge bases and machine learning. 4. Work Plan The work
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-516Geofield Contact City Caparica Website https://www.fct.unl.pt/ Street Campus de Caparica Postal Code 2829-516 STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More share options E-mail Pocket
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Caparica Website https://www.fct.unl.pt/ Street Campus de Caparica Postal Code 2829-516 STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More share options E-mail Pocket Viadeo Gmail Weibo
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Caparica Website https://www.fct.unl.pt/ Street Campus de Caparica Postal Code 2829-516 STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More share options E-mail Pocket Viadeo Gmail Weibo
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the different study cycles, namely those involving the design and implementation of new structures and equipment aimed at improving teaching and learning processes in the area covered by the competition. III
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of Chemistry Website: https://www.fct.unl.pt/faculdade/departamentos/departamento-de-quimica email: dq.secretariado@fct.unl.pt Telephone: (+351) 212 948 575 Call for Applications (Portuguese and English