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, Environmental sciences, or a closely related field. Proficiency in programming, particularly in Python, is essential. Knowledge of GIS (QGIS or ArcGIS). Experience working with spatial data, shapefiles, raster
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written and oral. Experience with computational tools commonly used in scientific research (e.g., MATLAB, Python, or similar). Above all, a genuine enthusiasm for science and discovery, particularly in
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100%, Zurich, fixed-term In the newly established Brain-Body Regulation Lab at ETH Zurich (Department of Health Sciences and Technology), we focus on developing non-invasive (self-regulation
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Theory, Queuing Theory, Age of Information), Network Calculus, Graph Theory, Convex and Non-convex Optimization, Approximation Algorithms. An excellent Master’s degree in Computer Science, Engineering
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among research groups Establishing mechanisms to gather input, needs, and feedback from community members Managing the ETH Zurich side of the Joint Doctoral Program on Learning Sciences (JDPLS ), and
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utilises cutting-edge recording techniques, including two-photon calcium imaging, high-density Neuropixels electrophysiology, and spatial transcriptomics, alongside computational analyses, to uncover novel
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most of the following: Bachelor's or (preferably) Master's degree in Computer Science, Engineering or a Social Science discipline combined with solid engineering skills 1–2 years of relevant work
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Computer Science, Artificial Intelligence, or related field. Proven experience in machine learning and neural network architectures. Strong programming skills in Python and familiarity with PyTorch. Experience with
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, computational genomics, or animal genomics. Experience with a programming language (e.g., python, R) and basic working knowledge with high-performance computing clusters is required. A MSc degree in genetics
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on partly artificial nature-based materials. These ecosystem services models will be integrated into a design-science loop (Urech et al., 2020; Salliou et al., 2024 ) supported by a 3D point cloud-based tool