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the Rheintal project Integrate CCUS and industrial processes into the energy system models Assess the energy system towards different metrics and optimization objectives such as cost and CO2 emissions Coordinate
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Interest in lab-automation and working with agentic AI (e.g. Claude Code, Codex) Excellent communication skills in English Strong academic track-record and publication history The ability to collaborate in a
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and working with agentic AI (e.g. Claude Code, Codex) Excellent communication skills in English Strong academic track-record and publication history The ability to collaborate in a multidisciplinary
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tasks As part of the NCCR-Network, you will contribute to the project aims in the areas of shaped CO2 adsorbents and sorbent ageing. Within the framework of the NCCR project with well-defined objectives
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. • Excellent Python programming skills and strong hands-on experience implementing, training, and evaluating deep-learning models and research codebases. A strong track record in machine learning or closely
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codebases. A strong track record in machine learning or closely related fields Excellent written and spoken English Ideally, the candidate also: Has experience in energy system modeling and optimization Has
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of this PhD project is to investigate lithium- and sodium-based solid-state batteries using muon-based bulk and interface characterization techniques. The main objective is to gain a mechanistic understanding
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results-oriented team player. Ideal profile includes following competencies and experience: Strong programming skills, deep statistical knowledge and a proven track record with machine learning Solid
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global concern because of their detrimental effects on the environment, ecosystems, and human health. This highlights an urgent need to track their footprints in the atmosphere which plays a key role in