73 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"UCL" positions at Aalborg University in Denmark
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Biological Learning Machine, which is headed by Professor Jan Østergaard. The goal is to develop novel information-theoretic methods for identifying and analyzing temporal and spatial patterns of synergy and
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competencies The applicant must hold a master’s degree in engineering and a PhD in a relevant field, such as electrical engineering, with expertise in physics-based modeling, machine learning, and optimization
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algorithms for speech enhancement using state-of-the-art machine learning techniques. You will design and evaluate models that leverage phoneme-level or discrete speech representations and conduct experiments
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students in its BSc and MSc programs, which are based on AAU's problem-based learning model. The department leverages its unique research infrastructure and lab facilities to conduct world-leading
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, mechanical and durability testing, and integration with advanced machine learning models. The postdoc will collaborate closely with CEBE’s parallel work packages. Experimental and analytical data generated in
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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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to have a strong interest in data analysis, and medical research, along with relevant academic background and skills within medical image analysis and machine learning that will enable them to contribute
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control venues such as the IEEE Conference on Decision and Control and IEEE Control Systems Letters, and in top machine learning conferences such as NeurIPS, ICML or AAAI, is expected. Proficiency in MATLAB
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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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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