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behaviour through these models using uncertainty quantification/machine-learning (UQ/ML) algorithms To optimise the manufacturing process with the help of the simulation tool To support in the development and
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experience in one or more of the following areas: machine learning, reinforcement learning, algorithmic trading, or data-driven modelling. Excellent communication skills: Solid written and verbal communication
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format for the unambiguous and machine-readable characterization of software interfaces and data models Selection and configuration of algorithms for annotating and organizing research data and software
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group focuses on developing strategies and algorithms to quantity biologic effects of particle radiation based on underlying physics, biology and physiology. Within the BMFTR funded project “BIOMICRO
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advantages for manipulation and locomotion, but current control algorithms do not fully exploit their capabilities. Most rely on approximations tailored for rigid systems or require extensive sensing and
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learning algorithms, and design of optical communication networks or power consumption and energy saving. The synergies of MATCH consortium act together to enable the thirteen DCs to become the next
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slicing. - Develop advanced AI/ML algorithms and data analytics techniques to automate and optimise exposure requests, adapted to available resources and real-time demand. - Propose and
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operate safely around humans. They offer unique advantages for manipulation and locomotion, but current control algorithms do not fully exploit their capabilities. Most rely on approximations tailored
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these frameworks to develop specific formulations and solution algorithms for the design of congestion pricing schemes using classical transport models and quantify the equity-efficiency trade-offs for congestion
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Vacancies PhD position on Stochastic geometric numerical methods Key takeaways Are you passionate about developing cutting-edge numerical algorithms at the intersection of geometry, stochastic