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system for thin, durable structural interventions. It can be deployed through conventional casting for standard applications and through 3D printing for complex or non-planar geometries. In parallel
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will include: Assemble and validate modular electrocatalytic reactors and analysis methods for realistic CO2 electrocatalysis, with a focus on parallel investigations and accelerated aging. Dissect
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complex or non-planar geometries. In parallel, circular end-of-life strategies will recover fibres, upcycle fines into new low-carbon constituents, and enable structural reuse. The project comprises 11
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of modern deep-learning architectures and training strategies, and experience designing and rigorously evaluating new machine-learning methods. • Excellent Python programming skills and strong hands
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advantage Proficiency in Python programming Interest in lab-automation and working with agentic AI (e.g. Claude Code, Codex) Excellent communication skills in English Strong academic track-record and
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, microscopy, or flow cytometry, is advantageous. Experience with advanced characterization techniques, such as scattering, spectroscopy, or related methods, is also advantageous. Programming and
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(Canada). The NCCR focuses on three key challenges: CO2 capture from air: Developing scalable, cost-effective processes to efficiently remove atmospheric CO2. High-temperature ammonia separation
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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 related fields
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assays. Experience in catalysis, programming and large data analysis is a plus. Excellent communication skills and fluency in English (written and oral). Our offer The project is planned for 3 years
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programming (e.g. Python or MATLAB) is an asset. A self-motivated and organized working style, with the ability to work independently while contributing effectively to an interdisciplinary and