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with global change. Research makes extensive use of global modeling tools (GEOS-Chem and CESM) and analysis of large observational datasets. The biosphere represents an important source of many reactive
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experience in developing software for scientific applications, data analysis, or real-time systems is desirable. Experience with parallel computing and optimization techniques for handling large datasets
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codebase used for training large generative neural network models. This role requires a strong background in machine learning, software development, and the ability to work collaboratively in a research
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precision and minimal interruptions throughout a life cycle. Incorporating predictive models and advanced control using data opens up exciting new possibilities in this domain. The research activities
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80%-100%, Zurich, fixed-term To support teaching, research and knowledge transfer, the IT Services (ITS) of ETH Zurich are working as a service organization in a large and complex IT environment
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of how non-canonical building blocks for exciting macromolecules can cross a highly selective cell membrane so they can be used in the cell, remains unanswered. We have in the past made large strides
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collaboration between several departments to comprehensively address the big questions of life’s origins and ubiquity. The Centre includes a dedicated gathering place to meet up and hold scientific discussions in
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-transportation system, we are looking for a: PhD Student in Data-Driven Policy Optimization for Transportation and Energy (100%) Project background Our energy and transportation systems are rapidly transforming in
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and interpretation of large-scale datasets, in particular next generation sequencing (NGS) data. The team covers raw data processing, high-performance computing, statistical evaluation, interpretation
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the state-of-the-art of model-based planning support for transport and urban systems under uncertainty. The doctorate will develop new tools and methods that integrate large-scale agent-based modelling