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Field
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methodologies or models from an engineering perspective, as well as scientific studies focused on understanding deep learning. This includes the development of novel applications of artificial intelligence
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multidisciplinary team. Ability to write publications, reports, and projects. Oral and written communication skills. Computer skills/programming/modeling would be a plus. Candidate Criteria Ph.D. in Chemical
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agricultural land to exit dairy production thereby opening opportunities for alternative agricultural enterprises. Learning Objectives: The fellow will gain experience in planning and conducting data collection
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Institute of Systems and Robotics, Faculty of Sciences and Technology of the University of Coimbra | Portugal | about 2 months ago
Engineering Research Field Engineering » Electrical engineering Engineering » Electronic engineering Engineering » Mechanical engineering Engineering » Computer engineering Researcher Profile First Stage
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Laboratoire de Physique des Interfaces et des Couches Minces (LPICM), UMR CNRS/École Polytechnique, | Palaiseau, le de France | France | about 2 months ago
(denoising, Mueller matrix calculation/decomposition) and AI-based diagnostic algorithms using machine/deep learning. The primary challenge will be to deliver practitioner-relevant cervical images in under 0.5
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algorithms and methods for adaptive and personalised feedback, modelling learning behaviours with sequence and deep learning methods, and generating interpretable insights through novel analytics and
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or application of machine learning models, particularly those focused on causal inference and decision-making; Prepare academic publications and participate in the dissemination of research findings; Collaborate
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of machine learning, simulation-driven testing, and iterative calibration based on real-world datasets. Contribute to scholarly publications, technical documentation, and progress reports required by funding
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models, machine learning, and/or programming in R or equivalent programs is an advantage but not a requirement. Alongside developing own research ideas, applicants should be capable of turning those ideas
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models, machine learning, and/or programming in R or equivalent programs is an advantage but not a requirement. The evaluation of applicants primarily hinges on their documented academic qualifications and