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are curiosity-driven especially interested in interdisciplinary research, eager to continuously learn with critical thinking and explore new ideas while collaborating with a team Language Skills: Fluent written
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Candidates will prepare a doctoral thesis in the field of neuroscience (project duration: four years). Research topics are olfaction, vision and acting, robotics, learning and memory, cortical and synaptic
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relevant aspects of cancer development and therapy Perform state-of-the-art in vitro organoid and in vivo experiments with single cell readouts Learn and apply a wide spectrum of genetic, molecular and cell
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to the best research institutions around the world. Continuous scientific mentoring by your scientific advisor as well as feedback and wide-ranging expertise from the whole group in multiple facets of quantum
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: to develop ideas and leaders that transform the world—from the very center of business. Our ever-evolving curriculum - featuring pioneering courses, STEM certification, and immersive experiential learning
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(density functional theory and ab-initio molecular dynamics simulations) with artificial intelligence techniques to parameterize machine learning force fields and kinetic Monte Carlo methods to model
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Supervisors: Prof. Gabriele Sosso, Dr Lukasz Figiel, Prof. James Kermode Project Partner: AWE-NST This project utilises advancing machine learning techniques for simulating gas transport in
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calculations of well-characterized 2D materials, simulations of electron microscopy images, and machine learning methods to reconstruct the 3D atomic positions of materials from a 2D microscopy image. The
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is to address these challenges by developing innovative integrated chassis controllers and processes that seamlessly coordinate multiple actuators from the outset. The research will explore advanced AI
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, criterion handling and machine learning. Topic The main research objective is to contribute to the development of responsible AI, with a strong focus on trust and confidence handling when dealing with data