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learning-based computer vision algorithms and software for object detection, classification, and segmentation. Key Responsibilities Participate in and manage the research project together with the PI, Co-PI
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early detection is a need that needs to be addressed using advanced sensors. The candidate will apply machine learning and IA methods to anticipate the evolution of the discharges. This project aims
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offers excellent researchers who have recently completed their PhD the chance to continue their research career at CTU. Fellows receive a two year fellowship and become members of a team led by a mentor
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developing new machine learning methodologies that tackle unique computational problems in healthcare applications. We use large real-world complex datasets, including data extracted from electronic health
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level. Successful candidates will teach and supervise students who are serving officers and civil servants in the UK and allied armed forces and partners. There are also opportunities to contribute
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require new mathematical machinery. LOGSMS will combine diverse tools from discrete mathematics, learning theory and machine learning, thus facilitating the design and analysis of such models. PhD position
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essential, while experience with machine learning is advantageous but not strictly required. Excellent English skills, both in verbal and written communication, are required for the project. We are looking
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application! We are looking for a PhD student in Statistics with placement at the Division of Statistics and Machine Learning, Department of Computer and Information Science. Your work assignments As a PhD
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for the PhD admission is available at TalTech´s web-page: https://taltech.ee/en/phd-admission The following application documents should be sent to tarmo.soomere@taltech.ee CV Motivation letter Degree
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federated learning, AI security and privacy, quantum machine learning (QML), robotics, and/or AI-driven discovery in science and engineering (e.g., genomics, bioinformatics, drug discovery, infectious disease