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section Energy Technology and Computer Science, where you will have around 20 colleagues with a mix of research and industrial experience. We work with research, innovation, technology implementation, and
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with researchers at DTU and KTH, you will help develop an integrated decision-support system that: Uses real-time sensor data and AI models to assess risk scenarios. Dynamically recommends optimal
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within the broad topics of modelling tool-workpiece interaction in mechanical material removal processes, zero-defect manufacturing, machining system performance characterization as well as on-machine and
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both technical insight into data modeling and a solid understanding of how real-world engineering data is generated, structured, and used. We are seeking motivated candidates with strong programming
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qualifications As our new colleague in our research team your job will be to develop novel computational frameworks for machine learning. In particular, you will push the boundaries of Scalability, drawing upon
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Job Description Do you have a background in bioinformatics or AI/ML? Do you wish to do a PhD whereby you use your computational skills to discover new insights in industrially important bacteria
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2025 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description We are looking
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a team of 25 colleagues dealing with CCUS, and industrial partners in Denmark as well as abroad. Your primary tasks will be to: Apply AI in context of capture solvent modelling Understand and analyse