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-camera, home-based markerless system Test the algorithm across lab and home-recorded environments to assess real-world performance Design clinician-facing visualization tools ensuring privacy-by-design
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help develop new computational models that integrate molecular reaction networks with AI/ML algorithms in order to predict patient-specific cardiac remodeling and heart disease outcomes across human
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expected to actively contribute to the project, work collaboratively as part of the research team, and perform the following major tasks: Conduct theoretical analysis, algorithm development, and simulation
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Responsibilities Conduct research in computational methods for environmental and engineering applications. Develop and analyze numerical algorithms, reduced-order models, and machine-learning-enhanced simulation
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(Automated Design of Algorithms) group in the machine learning clusters at LIACS, Leiden University, and supervised by Jan van Rijn and Holger Hoos. You will be working intensely with other project members
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safety-oriented control algorithms. · Investigate thermal management, fire suppression, and propagation-mitigation strategies for safer battery module and pack design. · Prepare technical reports
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that amplify human potential. The successful candidate will engage in innovative research projects in ML, focusing on developing novel ML algorithms, enhancing human-AI collaboration, and exploring systems
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in innovative research projects in ML, focusing on developing novel ML algorithms, enhancing human-AI collaboration, and exploring systems tailored to dynamic, human-centered environments. They may
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for building energy-efficient and robust brain-inspired, autonomous, and cognitive systems and intelligent vision systems, including efficient learning and inference of complex AI/ML algorithms, specialized
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will have a strong background in wireless communication, signal processing, and machine learning. They should also possess the skills necessary to develop complex models, algorithms, and simulations