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and physical principles of negative ion mode LC-MS/MS-based peptide analysis. The project combines method development and mechanistic exploration with downstream applications in proteome
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expected, as well as teaching in other study programmes at Aalborg University. Your competencies We are seeking motivated and talented candidates with a solid foundation in AI methods and mathematics, and a
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one or more of the following theories/methods: - wave-packet quantum dynamics (e.g., AIMS or MCTDH programs) - mixed quantum-classical dynamics, such as non-adiabatic MD (e.g., SHARC program) - density
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electronic states Experience with one or more of the following theories/methods: - wave-packet quantum dynamics (e.g., AIMS or MCTDH programs) - mixed quantum-classical dynamics, such as non-adiabatic MD (e.g
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solutions with emphasis on structural performance. Circular design and reuse of structural concrete elements. Behaviour and development of design methods for structural concrete. Design and strength
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learning potentials (MLPs). You will develop geometric graph manifold learning methods and utilize those to learn from heterogeneous quantum mechanical datasets. You will implement and benchmark state
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Job Description The Computational Protein Engineering (CPE) group at The Novo Nordisk Foundation Centre for Biosustainability (DTU Biosustain) is developing novel methods to engineer proteins more
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industry or academia. Your tasks will include conducting research on machine-learning-based methods for mitigating impairments arising from system components and transmission media in quantum communication
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publicly held (listed) companies. The department's researchers collaborate on specific research projects using a variety of quantitative as well as qualitative methods. Teaching responsibilities
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, current methods are either static, rely on heavy offline training, or fail to adapt to changing environments. This PhD project will develop intelligent software agents capable of autonomously optimizing