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software tools, including applications in geoscience, optimization, and techno-economic modeling. Guide the team in modern software development practices (e.g., version control, documentation, testing
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components, oxidation control, as well as the feasibility and application potential of multi-constituent nanopastes. This PhD project runs over 4 years with a final degree granted by ETH Zurich.
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have found intriguing successes in biosensing, control switches, signal amplifiers and modulators, and high-performance photocatalysis. The conventional plasmonic materials include noble metals, e.g
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, quality control, and preparation for publication. The chance to participate in future field campaign measurements, gaining practical experience with data collection. A collaborative work environment with
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processes in the laboratory. Current focal areas of the group include the evolution and control of antibiotic resistance, evolution and spread of plasmids, and viral diversification. Job description You will
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experience in statistical analysis and implementing machine and deep learning models using Keras/TensorFlow and/or PyTorch. You have experience in collaborative coding, version control, and utilizing computer
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advantageous): Mechanical design using CAD software (e.g. Fusion 360, SolidWorks, NX) LabVIEW for measurement and control applications In addition to your technical expertise, we value a collaborative and
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software development practices, including version control systems, debugging, testing, and deployment. Excellent problem-solving abilities and strong analytical skills. Ability to work effectively in a team
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, seismological monitoring products management, and quality control using industry-standard platforms such as SeisComP, SeedLink, and FDSN web services. The successful candidate will also support the development
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in agricultural sciences, micrometeorology, greenhouse gas exchange, or remote sensing. Relevant research experience can be based on observations, modelling, or statistical analyses. Excellent command