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Description REALISE - Bridging Igneous Petrology and Machine Learning for Science and Society About the REALISE Doctoral Network REALISE will train 15 Doctoral Candidates at the interface of igneous petrology
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Engineering, Computer Science, Telecommunications, or related areas. Solid background in signal processing, wireless systems, applied mathematics, and/or machine learning. Proficiency in programming (e.g
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(Python or C/C++) with experience in systems engineering and software development. Solid knowledge of both basic and modern methods in machine learning, NLP and computer vision, including supervised and
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Job type: Principal Investigator Qualification: PhD Job duration: fixed 5-year term (can be extended for additional 4-years upon positive evaluation) Job hours: full-time Discipline: Life Sciences
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Development of innovative experimental model systems for mechanistic investigation and translational validation of microbiome-mediated processes Advanced AI and machine learning frameworks for integrative multi
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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 The research program involves the study of machine learning
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experience with EB-PBF systems is considered an asset) Python programming Statistical learning / machine learning / machine vision / Artificial Intelligence methods Image and signal processing (familiarity