Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- INESC TEC
- INESC ID
- University of Stavanger
- UiT The Arctic University of Norway
- Universidade de Coimbra
- Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID
- Basque Center for Macromolecular Design and Engineering POLYMAT Fundazioa
- Basque Center for Macromolecular Design and Engineering, POLYMAT Fundazioa
- Institute of Systems and Robotics-Faculty of Sciences and Technology of the University of Coimbra
- Nanyang Technological University
- Universidade de Aveiro
- University of Oslo
- 2 more »
- « less
-
Field
-
23 Dec 2025 Job Information Organisation/Company INESC ID Research Field Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Positions Master Positions Country Portugal
-
of the state of the art in machine learning for generation of artificial data; - identify and select the appropriate methods for the study in question; - develop the research capacity through the application
-
of the Grant are:; 1) To apply machine learning algorithms for the diagnosis of faults and malfunctions in photovoltaic plants, using data from SCADA systems combined with synthetic data from digital twins (DT
-
Python for scientific computing – experience with data analysis and basic signal processing – foundations in machine learning and interest in developing advanced AI models – familiarity with Linux
-
Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 28 days ago
engineering Researcher Profile First Stage Researcher (R1) Positions Master Positions Country Portugal Application Deadline 16 Dec 2025 - 23:59 (Europe/Lisbon) Type of Contract Not Applicable Job Status Not
-
Machine Learning components of the CONVERGE project toolset.; - Assist in executing integration tests across different hardware and software modules.; - Contribute to the structured collection and
-
) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: Development of novel Machine Learning techniques applied in systems/networks research, which includes, but is not
-
of the state of the art in machine learning for generation of artificial data; - identify and select the appropriate methods for the study in question; - develop the research capacity through the application
-
economic assessments machine learning or proxy-model based methods field scale simulation geological features geomechanics reactive flow The PhD fellow are not expected to master all these topics. Project
-
domain in the design of deep learning algorithms for cardiovascular disease detection. 4. REQUIRED PROFILE: Admission requirements: Master’s degree in Biomedical Engineering, Computer Engineering