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then be used in a learning framework to design an automatic controller to optimize the usage of the sluice under various conditions. The other project will address challenges related to Sustainable Water
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by the Danish EUDP project “RePower-HPC.” Future AI and high-performance computing (HPC) systems demand unprecedented power levels driven by massive data processing. A key challenge is enabling
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support for professionals at Aalborg University! This interdisciplinary project investigates how generative AI can be incorporated into the building design and operation process. Particularly, we seek
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The Section for Electrical Energy Technology at the Department of Electrical and Computer Engineering (ECE), Aarhus University, is in a phase of rapid growth in both education and research
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in electrical engineering, computer engineering, computer science, or similar. Strong background in communication systems, optimization, or machine learning for networked systems. Experience and
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generation Developing and optimizing generative models for de novo binder design Collaborating closely with wet lab scientists who will express and test the designs that have been created Developing scalable
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to predict bacterial growth from protein sequence and compound molecular structure. Applying generative and predictive models to propose novel compounds optimized for broad-spectrum activity against diverse
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to improve and optimize stem cell differentiation and manufacturing. As our new colleague you will be part of a diverse and multi-disciplinary team, which is engaged in machine learning and has a drive to make
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inorganic syntheses Develop and optimize electrochemical experiments and measurements Characterize materials and compounds using standard analytical techniques Analyse data and document results Collaborate
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/MS experiments, with emphasis on negative ion mode Develop and optimize fragmentation strategies for peptide analysis under collisional- and electron-based dissociation regimes Investigate gas-phase