12 industrial-management "Technical University Of Denmark" Postdoctoral positions in Denmark
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, plant and planetary health. The microbial diversity in different niches is enormous, and it is not all bacteria or viruses that are harmful and many are even beneficial. We are constantly faced with
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collaboration with our team. You will: Develop ML methods to handle conditional data generation mechanism in the development pipeline, and for optimization and simulation Develop ML methods for uncertainty
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, Bash). Experience working in a Unix/Linux environment, including setting up and managing High Performance Computing (HPC) clusters. Familiarity with metagenomic data analysis and machine learning
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; Participate in project management and funding acquisition; Facilitate ad-hoc tasks within the section’s responsibilities in teaching and research; Take part in publication of research results. You should have
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Job Description The HyCheese project at the DTU National Food Institute brings together industry partners (Novonesis, FOSS, KMC) and academic collaborators from the University of Copenhagen (KU) and
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islands’, you will become part of a vibrant and growing STS environment at DTU’s Department of Technology, Management, and Economics, the Section of Science & Technology Studies. The project is funded by
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their efficiency, reducing size, and improving thermal management for data center power applications. In this project, you will explore the creative power solutions for low-voltage high-current VRMs, particularly
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Monitoring and Modelling solution for data-driven hOlistic management of urban water quality). At DTU Sustain you will contribute to creating digital solutions that will give urban water managers access to all
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. You are enthusiastic about enabling high-quality data science and management (data base systems, data pipelines, version controls, Github, FAIR data) You are an effective communicator, a good
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candidate will have the opportunity to collaborate closely with our Danish industrial partners on innovative use cases, including advanced condition-based monitoring in industrial settings and speech