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. after the interviews. Two outputs. This could be your MSc thesis, a coursework, or anything else you consider worth showing (e.g. code, poster, etc.). Please note that we exclusively accept applications
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of generative AI algorithms for manufacturing Collaborate with an interdisciplinary team to transform research results into innovative solutions Develop high-quality code and build the basis for our industrial AI
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-level algorithms on top of existing networks using sonar imaging Testing, analyzing and proposing improvements of the networks and implementing them Make pioneering algorithms for sonar perception ready
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this position, and career goals Contact information of 3 potential referees Curriculum Vitae Publication list A copy of your M.sc. or PhD certificate Coding sample / Github account / any other relevant
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particles, AgI-containing particles). Analyzing in situ data (holographic imagers) and ground-based remote-sensing data (cloud radar) to assess warm cloud susceptibility to aerosol perturbations. Quantifying
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, perform the evaluations hand-in-hand with the domain experts, and eventually release open-source code and the associated documentation, write research papers or technical reports as appropriate, and
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have a strong background in quantitative methods and are excited to code. You are interested in topics of global poverty and inequality. You have a good knowledge of the statistical software R and/or
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. Profile Enrollment as a student at ETH Zurich or the University of Zurich in a relevant field, such as computer science, engineering, economics and mathematics Intermediate coding skills in R, Stata
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-particle imager, radiosondes, sonic anemometers, flight logbooks of drones and the tethered balloon system) and remote sensing platforms (e.g., cloud radars, ceilometer, microwave radiometer). Organizing and
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. Potential research topics include: Use of hyperspectral reflectance for evaluating leaf functional traits. Integration of hyperspectral imaging with genome-wide association studies (GWAS). Detection