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relevant background within control, building, or HVAC engineering. A background in applied mathematics can also be relevant if there is a strong focus on data-driven modeling, machine learning, and control
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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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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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of employment for positions such as postdoctoral fellow, research fellow, scientific assistant and specialist candidate Preferred selection criteria Experience with machine learning and relevant tools, such as
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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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up exciting career opportunities? Are you interested in cable technology and condition monitoring, and do you have strong competence in signal processing and machine learning? As a PhD candidate with us, you
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hydrogenerators”. The project is linked to the new research center FME RenewHydro . You will join the research group Electrical Machines and Electromagnetics (EME) at IEL, where we foster an open, inclusive, and
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Candidates, Postdoctoral Fellows and permanent academic employees within the Department. This support aims to help develop the academic careers of female employees, and is also made visible to our student body
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Women in Science . The group is focused on supporting female Research Assistants, PhD Candidates, Postdoctoral Fellows and permanent academic employees within the Department. This support aims to help
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for Energy Technology, IFE). Duties of the position Carry out research of high quality within the scope described above. Develop mathematical models and computer code for optimization and simulation of energy