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and system optimization. Perform air and water balancing and make appropriate operational adjustments. Identify and correct deficiencies in pneumatic, electrical, airside, and waterside systems
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tasks, project documentation, build, installation, performance monitoring, optimization, troubleshooting and maintenance of a variety of systems of the network and network firewall. Build, install
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Veterinärmedizinische Universität Wien (University of Veterinary Medicine Vienna) | Austria | 17 days ago
position within a Research Infrastructure? No Offer Description Job Summary/offer: To optimally use the resources in veterinary care, it is important to capture, preprocess, and model the existing data
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Optimization of production processes with regard to product
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of coordination mechanisms that will evolve in alignment with ICFO’s digital transformation and process optimization initiatives. The role requires the ability to operate with autonomy, influence, and a strong
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Apply now Job no:539583 Work type:Full Time Location:Sydney, NSW Categories:Post Doctoral Research Associate The Opportunity: The Postdoctoral Research Fellow will join a dynamic, collaborative team
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chemistry and machine learning approaches to investigate innovative catalytic systems, with a focus on biomass-related areas Optimization of homogeneous and heterogeneous catalytic processes using high
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. The successful applicant will develop a predictive pipeline using atomistic modeling and machine learning to identify optimal "seeds" for directing crystal growth, followed by rigorous experimental testing
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the project leader in the research project – “Green energy-driven decarbonization in aviation: operational research, economic analysis, and policy perspectives”. Qualifications Applicants should have: (a
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Mathematics at the University of Twente. You will work under the supervision of Dr. Gregor Gantner on a project dedicated to advancing the field of adaptive methods for time-dependent partial differential