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on the development of AI models for analysis of cardiac CT scans, with the aim to explore how machine learning models can quantify cardiovascular disease and predict future events from CT scans. The project will
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computer science. The candidate is expected to have solid knowledge in most of the following areas: Robotics Control theory Deep Learning & Machine learning Modelling and control of soft/continuum robots Experience
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of the following areas: Robotics Control theory Deep Learning & Machine learning Modelling and control of soft/continuum robots Experience with embedded systems programming (Preferably) with a strong background in
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experience in several key languages, e.g., Rust, C++, or Python (not MATLAB), algorithms, and machine learning is necessary as well as excellent communication skills in English. Applicants with experience in
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team. Significant software development experience in several key languages, e.g., Rust, C++, or Python (not MATLAB), algorithms, and machine learning is necessary as well as excellent communication
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Computer Vision There is growing trend towards explainable AI (XAI) today. Opaque-box models with deep learning (DL) offer high accuracy but are not explainable due to which there can be problems in
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has more than 600 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
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modifications using high-resolution mass spectrometry and AI-based de novo peptide sequencing. Develop and apply machine learning models to predict protease activity and substrate specificity, integrating protein