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Field
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of the extraction and beneficiation system. This work will require an understanding of mining processes, mathematical modeling of flows and extraction decisions, and the use of machine learning algorithms to predict
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training algorithms and AI architecture. Image reconstruction, segmentation, and classification. High performance computing for spatiotemporal data. Major Duties/Responsibilities: Develop foundation AI
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About Us We are seeking experts in medical image deep learning to join our team and help develop novel computationally efficient segmentation algorithms. We welcome application from individual with
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funded by a EU programme Reference Number 304--1-14162 Is the Job related to staff position within a Research Infrastructure? No Offer Description Join a research team developing state-of-the-art open
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(e.g., based on physiological signals or direct inputs from occupants) and developing algorithms, including machine learning methods. The work will include statistical modelling, data-driven modelling
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metagenomics assembly” funded by the Research Council of Finland in the research group of University Lecturer Leena Salmela. We develop models, algorithms and data structures for high throughput sequencing data
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models, analysing structural properties, and developing innovative algorithms with both theoretical rigor and practical relevance. Where to apply Website https://www.academictransfer.com/en/jobs/354359
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sparse algorithms. The successful candidate will contribute to advancing secure, trustworthy, and efficient AI solutions for scientific applications. Key responsibilities include developing state
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committed to an educational system based on the highest standards of teaching and research in fields related to the sustainable economic development of Morocco and Africa. More than just a traditional
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and analysis of mathematical methods for novel imaging techniques and foundations of machine learning. Within the project COMFORT (funded by BMFTR) we aim to develop new algorithms for the training