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interest and documented skills and experience in using computer-based tools to analyse, simulate and predict capture performance of active and passive fishing gears. A track record of publishing in peer
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neuro-adaptability with changes in cortical manifestations during an intervention (e.g., non-invasive brain stimulation) for symptom reduction. Large-scale data analysis (e.g. machine-learning) will
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to collaborate with industry partners, teach at undergraduate and graduate levels, and supervise Master's, and PhD students. Candidates will become part of a collaborative work environment within and outside QGG
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for applicants who have obtained their PhD within the past 4 years, have a good publication record, and have proven their expertise on computational electrodynamics and the theory of light–matter interactions
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respectful environment providing room and support for your interdisciplinary, professional and intellectual growth. Your competences You have academic qualifications at PhD level, for example within
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qualification, you must hold a PhD degree (or equivalent). The successful candidate must moreover exhibit the following professional and personal qualifications: Strong background within machine learning learning
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to the project deliverables while also supporting project management tasks, including deliverable preparation, milestone tracking, and communication across the consortium. Qualifications and requirements PhD
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offer a unique opportunity to contribute to high-impact research in drones, AI, and human-computer interaction. Successful candidates will join a dynamic and inspiring international research environment
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provide assistance in organising workshops and advisory board meetings. The post is for two years and represents an exciting opportunity to acquire valuable research experience, to contribute
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simulations using, e.g., COMSOL, Lumerical, or other Maxwell solvers. Experience with machine learning algorithms is an advantage but not required. General qualifications Scientific production and research