203 machine-learning "https:" "https:" "https:" "https:" "RAEGE Az" PhD scholarships in Netherlands
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, electrical engineering or simila,r with an affection for machine learning; You are an independent and original thinker with a creative mindset; You are a fast thinker with excellent analytical and
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description As a PhD candidate, you will: - Develop and train deep-learning
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. Methodological Approach Candidates will develop and apply state-of-the-art machine learning techniques, including deep learning, representation learning, variational autoencoders, and graph-based models. A strong
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of academic skills through teaching courses and supervising master/bachelor theses within the department. Where to apply Website https://www.academictransfer.com/en/jobs/358940/phd-candidate-in-mathematical-o
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engineering Engineering » Simulation engineering Researcher Profile First Stage Researcher (R1) Country Netherlands Application Deadline 5 Feb 2026 - 22:59 (UTC) Type of Contract Temporary Job Status Not
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to this email address or via LinkedIn. They will not be taken into consideration. You can apply via the button below. About the department You will be a part of the Photo Catalytic Synthesis lab (<https
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public interest. You can find more information about this assessment on our website about Where to apply Website https://www.academictransfer.com/en/jobs/359380/phd-position-scenario-planning
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recruitment of personnel. We do this, among other things, to prevent the unwanted transfer of sensitive knowledge and technology. The assessment is based on information … Where to apply Website https
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… Where to apply Website https://www.academictransfer.com/en/jobs/359399/phd-position-in-high-performanc… Requirements Additional Information Website for additional job details https
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disconnectivity in brain networks relates to symptom networks and recovery trajectories in psychiatric patients. Apply and further develop methods from network science, machine learning, and computational