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economically while supporting a sustainable grid. This PhD project aims to leverage cutting-edge optimization, control and machine learning methods to optimally integrate vertical farms in these emerging
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close relation with another PhD student in Université de Lille, France. The selected candidate will have the opportunity to learn form a consortium of 8 institutions (10 Beneficiaries, 3 Partner
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using machine learning or any other AI technique. Knowledge of CCS. Good oral and written presentation skills in Norwegian/Scandinavian language equivalent level B2. Personal characteristics To complete a
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on ROS2 (Robot Operating System) and best practice of use of Github. Knowledge and skills on methods in numerical optimization, machine learning, as well as knowledge on marine power and control systems
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to your work duties after employment. Required selection criteria You must have a professionally relevant background in algorithms, machine learning, database systems, or data mining, with a research
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machine learning models Experience in X-ray or electron-based materials characterization methods Personal characteristics To complete a doctoral degree (PhD), it is important that you are able to: Willing
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criteria Prior publications within relevant fields Strong problem-solving skills and a demonstrated capacity for innovative thinking Experience and expertise in machine learning Personal characteristics
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engineering Engineering » Civil engineering Technology » Safety technology Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Norway Application Deadline 28 Mar 2025 - 23:59 (Europe
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under the “Cryptographic elements of trustworthy AI” project. The main research objectives for the project are the following: Analyze security of Machine Learning (ML) models against data modifications
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Electrical Machines and Electromagnetics (EME) Complete academic training consisting of coursework corresponding to a minimum 30 ECTS. 6 months of duty work may be offered to the PhD candidate with clear