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processing conditions Apply data-driven and machine-learning methods for multi-objective optimization of efficiency, reproducibility, and operational stability Study intrinsic material stability
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and applying optimisation methods, such as model predictive control, multi-objective optimisation and, where appropriate, reinforcement learning Investigating suitable model-reduction and approximation
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particularly encouraged to apply. As an international intellectual community that encourages diversity, openness and creative learning, DKU welcomes outstanding faculty from around the world who contribute
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LTS2 Lab https://lts2.epfl.ch offers a highly motivating, interdisciplinary scientific environment with many opportunities to interact between different projects and researchers, and has an
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transformative potential in medicine, biotechnology, and the life sciences. We seek outstanding candidates with an innovative and impactful research program integrating deep learning and AI-driven
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opportunity to work at the forefront of brain-inspired control and soft robotics. At DTU, you will develop novel control architectures that combine model-based methods, reinforcement learning, and
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a PhD student Our group and research You will join a dedicated research team focused on machine learning applications in crystallographic method development and applied structural science on
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integrate rare protein coding genetic association data with functional and machine learning-derived features 4. Developing methods to characterize the genetic architecture of autism Salary and Benefits
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., near-miss detection, predictive crash risk, multimodal exposure estimation). · Design, implement, and validate AI pipelines (computer vision, tracking, spatio-temporal modeling, edge learning
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closely related field, completed by the start of the position Have practical experience in machine learning with Python, including training neural networks in PyTorch or a similar framework Have a solid