PortugalProfessional assignment

Job opening for the recruitment of a research assistant, under a fixed-term public service employment contract.

Universidade Politécnica de Viana do Castelo (UNIPVC)

Deadline

28 October 2026

Description

Offer Description: Competition for the recruitment of a Research Assistant, for a period of 3 years, under the terms of paragraph 2 of article 6 of the PhD Hiring Regime (Decree-Law No. 57/2016, 29.08), always subject to the operating period of the project in which the research is included, namely, Activity 3 of the Project “Maintenance4SEA 4.0 - Development of methodologies and technologies for predictive maintenance in offshore energy production systems”, financed by the NORTE2030 Operational Program, within the scope of the notice NORTE20302024-13 - SACCCT - Integrated ICDT Projects - APNOR Consortium, with the objective of developing methodologies and technologies for the predictive maintenance of components and structures of offshore renewable energy production systems. In accordance with the provisions of subparagraph a) of paragraph 1 of Article 11 of Decree-Law No. 57/2016, of August 29, it is hereby made public that, by order of the Rector of the Polytechnic University of Viana do Castelo, dated July 27, 2026, then President, authorization was granted for the opening, for a period of 10 working days, of a competition for the recruitment of a Research Assistant, under a fixed-term public service employment contract, in accordance with paragraph 2 of Article 6 of the Contracting Regime, always subject to the operating period of the project in which the research is included, aiming to fill a job position in the Scientific Area of ​​Electrical Engineering, Electronics and Telecommunications, Industrial Informatics, or related fields. Validity of the competition - The competition is valid only for filling the indicated job position, that is, the validity of the competition expires when the job position is filled. Applicable legislation - This competition is governed by the provisions of Decree-Law No. 57/2016 , of August 29, with the amendments introduced by Law No. 57/2017 , of July 19, and subsidiarily by the General Law on Public Service Employment (LTFP), approved by Law No. 35/2014 , of June 20, in its current wording, and by Ordinance No. 233/2022, of September 9. Requirements: Research Field Other Education Level PhD or equivalent Skills/Qualifications The general admission requirements are those set out in Article 17 of the LGTFP. The special admission requirements are: Holding a doctorate in Electrical Engineering, Electronics and Telecommunications, Industrial Informatics, or a related field. Specific Requirements The following are special admission requirements: Holding a doctorate in Electrical Engineering, Electronics and Telecommunications, Industrial Informatics, or a related field. If the qualification was awarded by a foreign Higher Education Institution, it must be recognized by a Portuguese Higher Education Institution, in accordance with the provisions of Article 25 of Decree-Law No. 66/2018, of August 16, which approves the legal regime for the recognition of academic degrees and diplomas of Higher Education, awarded by foreign higher education institutions, and subparagraph e) of paragraph 2 of Article 4 of Decree-Law No. 60/2018, of August 3, and any formalities established therein must be fulfilled by the date of the hiring act. If the candidate is not a native speaker of Portuguese or English, they must possess language skills at level C1 of the Common European Framework of Reference for Languages ​​(CEFR) in at least one of these languages. The candidate must also demonstrate that they possess: Experience in applied research and development activities in the areas of real-time embedded systems and multi-agent distributed systems (or related areas); Experience in orchestrating Edge-AI pipelines, including distributed inference management, optimization of computational resources along the edge-fog-cloud continuum, and coordination and scheduling mechanisms in distributed architectures; Proficiency in advanced Machine Learning methodologies, techniques, and tools applied to distributed systems and e

Sectors

Other

Source

Source: euraxess.ec.europa.eu

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