65 image-processing-and-machine-learning-"RMIT-University" Postdoctoral positions at Technical University of Denmark
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interest and documented skills and experience in using computer-based tools to analyse, simulate and predict capture performance of active and passive fishing gears. A track record of publishing in peer
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digital co-simulation platforms (e.g., Modelica-Python/Simulink) Applying machine learning and data-driven approaches to enhance the operation of district heating substations Participating in course
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simulations using, e.g., COMSOL, Lumerical, or other Maxwell solvers. Experience with machine learning algorithms is an advantage but not required. General qualifications Scientific production and research
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of dynamic operation, which is essential for effective system-level integration. The technology should have a high and stable electrochemical performance. Furthermore, mechanical robustness is a challenge
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Communication, Singal Processing, Low Power Electronics, Wireless Sensing, Low-Power System Design, Machine Learning & Edge Inference, Underwater acoustic communication. Furthermore, you have a proven record of
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for carbon cycling, ecosystem functioning, fisheries, and services such as CO₂ sequestration. Despite their importance, many of these processes remain poorly understood due to Greenland’s remoteness and
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approach will create a unique foundation for advanced data analysis, including AI, machine learning, and statistical modeling, aimed at uncover the key traits that define successful microbial biofertilizers
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circular plastics economy. Learn more about the project at https://inano.au.dk/about/research-centers-and-projects/enzync . Note that the current position is based at DTU, Lyngby. Further information may be
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and Mechanical Engineering (DTU Construct). In this role, you are advancing innovation by integrating material science, advanced processing techniques, and modelling to gain a comprehensive
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, including GKP state generation and nonlinear gates. EPIQUE (Horizon Europe): Cluster state generation on photonic integrated chips and its integration into a measurement-based Gaussian Boson Sampling machine