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Field
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statistical evaluation Machine learning analyses: implementation of established and new workflows Coordination of activities with Consortium partners, including presentation of results at consortium meetings
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for construction operations. The successful candidate will contribute to cutting-edge research in mixed reality (MR)-based simulation platforms, machine learning-based process optimization, and human-machine
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supervised by Dr. Ali Trabolsi Required Education, Certifications, Licensing or Training PhD in chemistry. Preferred Education, Certifications, Licensing or Training PhD in chemistry having research topic
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experience with software radios, 5G user equipment, VPNs, Tor, or other hard- and software relevant to the described systems an networks Up-to-date software development and machine learning skills, incl. work
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Vision, Robotics, Evolutionary Computation, Deep Reinforcement Learning, and Machine Learning. This should include a proven publication track record. You should also have: Research Associate: A PhD (or
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rigorous, collaborative research aligned with project goals. Develop and apply deep learning models, particularly in computer vision, NLP, and multimodal systems. Publish in peer-reviewed journals and
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considers factors such as (but not limited to) the specific grant funding and the terms of the research grant when extending an offer. PhD apply on Interfolio site For people in the EU, click here
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, and evaluation The ideal candidate will lead their own project, and also collaborate with and support 1-2 PhD students on their projects. The ideal candidate will also be interested in learning to write
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machine learning, Computer vision, Swarms, Autonomous Robots, hardware security, and Embedded systems development is desired. The successful applicant will work on various projects on robotics and computer
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Postdoc in modelling Greenland and Himalaya precipitation using machine learning Faculty: Faculty of Science Department: Department of Physics Hours per week: 36 to 40 Application deadline: 26