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project. The research will bridge both established and emerging technical expertise within the section, encompassing areas such as FPGA and neuromorphic computing, Edge AI, machine learning, power
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to work independently and collaboratively within interdisciplinary teams. Background in cybersecurity, machine learning, AI, or large language models (LLM) is advantageous but not a requirement
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medical images and other health data. The group develops and evaluates clinically meaningful decision support tools by integrating health data, domain knowledge, and machine learning. Key objectives include
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include data science management and development of novel and executing existing computational methods including machine learning and deep learning methods to integrate genomics, transcriptomics and
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transportation engineering, economics, psychology, computer science, social data science, machine learning, mathematics, and statistics. As a candidate, you should have a high potential for creative and
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broadly cover digital technologies within mathematics, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip
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of the following areas: Research and development within computer vision and machine learning. Research and development within UAS platforms, subsystems, and payloads. Software design and development (C, C++, Python
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Post Doctoral Researcher in Human-centred Large Language Models for Software Engineering, Departm...
The Section for Software Engineering and Computing Systems, at the Department of Electrical and Computer Engineering (ECE), invites applicants for a two-year postdoctoral position within the area of
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applications from researchers specializing in probabilistic and neuro-symbolic AI. Areas of interest include, but are not limited to: • Probabilistic machine learning • Deep probabilistic graphical models
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history analysis and possibly also with machine learning. Another specific example is statistical software development, e.g. implementing tools and algorithms for working with causal discovery