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Non-College Work-Study-Student Research Assistant - (STU001840) Student Research Assistant Department Name:D0019 Computer Sci & Engr Technology Description The Computer Science and Engineering
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on topics including molecular clouds and star formation. Candidates with experience in machine-learning and magnetic field observation/simulation are particularly welcome to apply. Experiences with (sub-)mm
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to, transient astrophysics, lensed stars, lensed supernovae, supernova cosmology, nature of dark matters, and advanced transient-detection/classification algorithms. Skills in machine learning and JWST/HST data
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require knowledge of both languages and you must be happy learn the other language if you are not experienced. We are not expecting you to be an expert in all forms of computer simulation and web deployment
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including OpenCV, Pointcloud library, Tracking filters, Computer vision techniques Experience with AI, deep learning and machine learning algorithms such as YOLO and Faster RCNN Experience with SLAM
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modelling of transport in WDM and compare predictions against experimental data. For both positions, we expect Machine Learning techniques to be used/deployed in the data analysis and in the creation
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, fiber optic networks and fiber optic network projects; Knowledge of the NEXTELCO platform; Knowledge and experience in optimization, machine learning and neural networks; Knowledge of programming in
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associate or bachelor’s degrees through a combination of in-person, online or blended learning. All of our system institutions place strong emphasis on service — helping to build healthier, more educated
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fault localisation and failure analysis (FA) techniques with Artificial Intelligence (AI)/Machine Learning (ML)/Deep Learning (DL) capability. You will work closely with our researchers, students, and
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project, namely tasks 3 “Data Acquisition and Processing” and 4 “Mechanistic and Machine Learning Models’ Conception and Evaluation”. The scholarship holder is expected to be able to carry out independently