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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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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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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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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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a great challenge in the ongoing quest for making future shipping sustainable. Are you also interested in ships, first-principle physics, artificial intelligence, and machine learning? Then this job
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required. Experience with finite-element method (FEM) and boundary-element method (BEM) is required. Experience with supervised machine learning in aeroelasticity is required. Programming skills, e.g
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Detection and Machine Learning (IEL) PhD in Power Grid Modelling for Net-Zero Energy Systems (IEL) PhD in Incorporating Distribution Grids in Multiscale Stochastic Energy System Models (IØT) PhD in Aspects
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will provide experimental input to the models and for validation. If appropriate and needed, machine-learning-based approaches may also be a part of the research activities, allowing for a combination of
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experiences and skills will be emphasized: Desired knowledge/experiences in: Working with diverse remote sensing data Data science topics particularly machine learning and deep learning. High Performance
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of mobile robot navigation principles Strong skills in data analytics, computer vision and machine learning Skills in scientific writing Applicants who have recently graduated with excellent results may be