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. The successful candidate will be involved in the gravitational wave astronomy research area as part of the GRAVITY research group, within the framework of the project "Ground-based Discovery Machines
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learning and deep learning. Specific Requirements PhD in acoustics. Knowledge of acoustical measurement techniques, as well as physical acoustics. Some experience in acoustic signal processing and machine
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..................................................................................................... up to 15 points <b>Machine</b> <b>learning</b> and optimization algorithms ............................................................... up to 10 points Section 3: Other Merits – up to 5...
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in Machine learning, Natural Language Processing, and/or Software Development. Applicants with an experience in one or more of the above academic fields are encouraged to apply. High proficiency in
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machine learning or computer vision, or be in the final stage of their PhD with a scheduled or imminent thesis defense. A strong publication record is required. We are looking for candidates who have
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for a short-term 2.5-month postdoctoral position (full-time) focused on developing and validating machine learning models that predict soil health and crop performance. The position will exploit datasets
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via machine learning Synthesis fire retardants and functional nanomaterials Preparation of fire-retardant polymers via polymerization or polymer process The candidate will acquire hands-on experience
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Python programming. ● Experience in monitoring code performance. ● 3 or more years of demonstrable experience in machine learning theory. ● Excellent communication and teamwork skills. ● Proficiency in
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Degree or equivalent Skills/Qualifications A Technical Degree or an equivalent in Computer Science, Telecommunication Engineering, or a related field with a strong academic background in Machine learning
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processes. • Apply machine learning techniques and advanced statistical analysis to extract knowledge from complex datasets. • Participate in the evaluation and optimisation of high-performance scientific