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, you must hold a PhD (awarded no more than three years prior to the application deadline*) in computer science, maritime transportation, or a related field, with a strong foundation in mathematics and
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The applicant should have a PhD degree in transport, operations research, applied mathematics, computer science, or similar topics. Experience with optimization, data-driven or machine-learning skills
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Qualifications To qualify for the position, you must have: A PhD in Structural Engineering, Building Materials, or a closely related field, awarded no more than three years before the application deadline* Strong
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-scale computational methods, and bioinformatics. The division is also expanding in the area of data science and machine learning. Our department continuously strives to be an attractive employer. Equality
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aviation. Your profile Required qualifications: PhD in aerospace engineering or a related field, with a focus on air traffic management or aircraft aeroacoustics, awarded no more than three years before
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Are you a passionate researcher looking to contribute to the advancement of life science and make a meaningful impact on health, sustainability, and innovation? Join us as a Postdoc at Chalmers
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Department of Chemistry and Chemical Engineering , contributing to a highly interdisciplinary research setting. We seek candidates with the following qualifications: PhD in materials science, physics, polymer
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of the Wallenberg Centre for Quantum Technology (WACQT, http://wacqt.se ). The core project of the centre is to build a quantum computer based on superconducting circuits. You will be part of the Quantum Computing
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and professors. Qualifications To qualify for this position you must have: - a PhD degree (or equivalent) in Applied Physics, Engineering Physics, Electrical Engineering or similar, awarded no more than
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to the application deadline. PhD in computer science, electrical engineering, biomedical engineering, or a related field. Experience in Python programming, natural language processing, and multimodal deep learning