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Field
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, technology, gastronomy, sports... among many others. Healthy Offering: choose from a variety of wellbeing focused activities to be the healthiest you. Selection process Deadline to apply: 06-11-2025 Additional
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scientific disciplines Collection, processing, analysis, and interpretation of scientific papers and reports Identification of risks and escalation of risks to a superior position You have (necessary
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infrastructures with early warning and blocking capabilities of DDoS attacks (SDPICaDDoS) Research Field Engineering » Communication engineering Engineering » Computer engineering Engineering » Electronic
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autonomous driving. Your profile Master's degree in Computer Science, Artificial Intelligence, Robotics, or related field Strong background in machine learning, deep learning, or computer vision Experience
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1 Research Fellowship (Master) - 101112877 - UPSTREAM - HORIZON-MISS-2022-OCEAN-01-04 - #NOVAID-B396
of the academic degree and the conversion of the final classification to the Portuguese scale (process regulated by Decree-Law No. 341/2007, of 12 October), or alternatively, to obtain equivalence/recognition
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Universidade Lusófona´s Research Center for Digital Human-Environment Interaction Lab | Portugal | 15 days ago
the Universidade Lusófona de Humanidades e Tecnologias, author of the opening of this call. Publication of the procedure observes that established by article 11 of Decree-Law no. 57/2016, of August 29, amended by
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Freire, Full Professor, hereby announces that the international selection process for the recruitment of one PhD researcher is open for a period of 10 working days, within the scope of the FLATFARE Project
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science, to deliver molecular mechanics force fields that bridge the gap to quantum mechanical accuracy for biological modelling and computer-aided drug discovery. They will develop electrostatic embedding
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(SFDI) and also from our custom-built photoplethysmography (PPG) sensor. Applicant should have experience in time-series processing with appropriate AI models (recurrent networks, LSTM) and experience in
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that provides timely and effective support to real-life policy processes. The successful candidate will become part of an interdisciplinary team and support the development of data and model assets which are used