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Your profile Candidates should have an exceptional academic record and a robust mathematical foundation. They should have published works at the main conferences in the field of machine learning
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learning with the physics of laser–matter interaction. Your developments will be directly validated through multiple experimental runs on state-of-the-art laser processing equipment. You will work closely
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. You will perform microstructural characterization of dry coated electrodes using physical and machine learning based methods and the electrochemical assessment of the electrodes in battery cells. Your
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, particularly on measurements and searches using jet substructure and development of advanced techniques in particle tagging, including applications using machine learning, and are expected to take leading roles
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promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and
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Apply machine learning techniques for data analysis and time-series forecasting Collaborate in a multidisciplinary team to accelerate functional thin film development Your work will be part of a larger
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Biljecki (National University of Singapore). Your key responsibilities will be: 1. Co-developing the research of work package 1. This work includes, a.o.: Developing deep learning models for the project’s
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Location: Sofia, Sofia 1784, Switzerland [map ] Subject Areas: Computer Science / All areas Quantum Computing / Quantum Computing Artificial Intelligence Machine Learning / Machine Learning Natural
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here You are able and willing to learn more about digital state-of-the-art methods quickly, preferably based on some previous experience, e.g., in using CAD software or a little programming Workplace