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research in one of the Department's key research areas: (i) Artificial Intelligence and Machine Learning; (ii) Big Data and Data Management; (iii) Computer Vision and Pattern Recognition; and (iv
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://cavecore.eu/ Your Research Project (DC4) You will work at the intersection of machine learning, control theory, and autonomous multi-agent systems to develop hybrid learning-based control strategies
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About the Opportunity Responsibilities: Teach selected master level courses of the Master of Science in Electrical and Computer Engineering (ECE) program of the ECE department at the Northeastern
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. The Machine Learning for Integrative Genomics team (https://research.pasteur.fr/en/team/machine-learning-for-integrative- genomics/ ) at Institut Pasteur, led by Laura Cantini, works at the interface of machine
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://www.maynoothuniversity.ie/physics/our-research . This position is part of the CARINA project which is funded through a Research Ireland Frontiers of the Future grant. CARINA stands for Combining Machine Learning with
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? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The candidate will be involved in the development and implementation of machine
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for this position will work as a member of an interdisciplinary team on research involving the use of statistical and machine learning methods for the development of Immune Digital Twins. There will be potential
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Science, or a related technical field Master's or PhD degree in Machine Learning, Computer Vision, or related areas will be advantageous Preferred Qualifications: Experience with biological/ecological
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responsibility of developing predictive tools based on machine learning for the analysis and interpretation of Raman vibrational spectra applied to battery materials. The successful candidate will design and
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conferimento di n. 1 incarico di ricerca scientifica di Fascia 1 presso la Sezione di Roma dell’INFN - 12 mesi Where to apply Website https://www.ac.infn.it/ Requirements Additional Information Eligibility