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Field
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necessary process in chip manufacturing and responsible for an estimated 40% of water consumption in a chip factory while using large volumes of polishing slurries which contain oxide nanoparticles
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methods to estimate the uncertainty in the daily predictions What do we expect from you? We seek a scientifically curious researcher who is passionate about understanding the environment. You should hold a
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in Computer or Data Science, Mechanical Engineering, Mathematics, Physics, Electrical and Information Engineering, or a related field – very good programming skills in Python – interest in topics
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complex biophysical processes on long timescales. We use data-driven methods for systematic coarse-graining of macromolecular systems, to bridge molecular and cellular scales. We work on a theoretical
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to develop a 3D-generative algorithm for pharmaceutical drug design by using or combining novel machine learning approaches? How would you integrate machine learning, physics-based methods in an early-stage
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Your Job: Support us in providing orientation knowledge for politics, industry, and society for the success of the energy transition by joining our team in the topic area method development
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computer-aided methods e.g. for data analysis Excellent cooperation and communication skills complete your profile; proficiency in English is essential Our Offer: We work on the very latest issues
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. Your tasks identify relevant satellite datasets of irrigated areas, as well as of hydrometeorological, land surface and vegetation variables apply modern statistical methods on these datasets to detect
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. Become a part of our team and join us on our journey of research and innovation! What
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students who would like to write their final thesis in the field of machine learning / computer vision. The primary goal of this master’s thesis is to develop an algorithm that can accurately and efficiently