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: Education: Bachelor in Biosciences, or Engineering degree in Computer or Data Sciences. PhD in bioinformatics, data sciences, machine learning or related areas. Experience: previous experience working with
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, United States of America [map ] Subject Area: Formal Methods and Machine Learning for Mathematics Appl Deadline: none (posted 2025/10/03) Position Description: Apply Position Description The Institute for Computer-Aided
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- Institute for Systems and Computer Engineering, Technology and Science, a private research institution, is accepting applications to hire a doctorate researcher for an undefined term resolutive contract
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University of Maryland, Baltimore County | Southern Md Facility, Maryland | United States | 8 days ago
: 495146 Application Instructions: Apply via Interfolio at: https://apply.interfolio.com/178333 Department: College of Engineering and Information Technology Computer Science and Electrical Engineering or
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together to develop solutions for the global challenges of today and tomorrow. Where to apply Website https://academicpositions.com/ad/eth-zurich/2026/phd-position-in-mechanochemica… Requirements Research
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multilingual AI, Translation quality evaluation using AI Teach undergraduate and postgraduate courses in Computational Thinking, Machine Learning and Natural Language Processing (NLP) for translators, LLM and
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the PhD physically at Thales, working directly with planners, engineers, and data teams on real production challenges. The PhD will be hosted by the Industrial Engineering and Management Sciences (IEMS
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intelligence, statistical learning, data mining, machine learning, database fundamentals, and related data models and queries. The IAD is the home of several graduate programs, including a Ph.D. in Computational
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Intelligent active gate driver for net zero energy systems (S3.5-ELE-Foster) School of Electrical and Electronic Engineering PhD Research Project Competition Funded Students Worldwide Prof Martin
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, integrative systems biology, and machine learning. Our research is focused on analyses of data generated within the biological, biomedical, biotechnological and life sciences areas. The section has extended