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acquisition and management. This role directly builds upon Ph.D. research by applying advanced 3D imaging, algorithm design, machine learning, software engineering and visualization techniques to a real-world
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learning, and innovative thinking. Join us at RCSI, where your contributions will be recognised, and you will be part of a dynamic team making a real impact on global health. About PRiCAN PRiCAN (Primary
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multimodal deep learning models that integrate imaging and clinical data to personalize treatment and follow-up strategies. In the Netherlands, around 75% of patients with an abdominal aortic aneurysm (AAA
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to religious and worldview diversity for individuals in public service such as administration, health care, correctional facilities or the armed forces. The position's mandatory work (25%) will consist
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Python, MATLAB, or C++. Experience with machine learning techniques, CAD, computational modeling, 3D printing, motion capture, and/or material testing. Proficiency in programming languages commonly used in
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visualization. Experience with GWAS, Bayesian modelling, and/or machine learning applied to biological data. Strong programming skills (R, Python) and ability to manage large-scale -omics datasets. Good
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collisions and maximize efficiency through innovative AI-based movement and maneuver planning. For the first time, innovative machine learning concepts, such as “shadow learning”, are being used. Appropriate
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materials; superconductivity; collective excitations (e.g., excitons, magnons, skyrmions); integer and fractional quantum (anomalous) Hall effects; machine learning approaches for quantum many-body problems
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the intersection of machine learning and genomics. The project involves the development and application of advanced machine learning and deep learning techniques to understand the sequence-function relationships
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-Phenomenology (hep-ph) , HEP-Theory (hep-th) , High Energy Physics , High Energy Theory , Machine Learning , Particle Physics , String Theory/Quantum Gravity/Field Theory , string-math Appl Deadline: 2026/03/31