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a broader effort to inform resilient market design and improve policy decision-making. Project background This position focuses on extracting and validating BOMs (Bills of Material) for medicines
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for recognizing handwritten mathematics, diagrams, and code, and manage systems that provide timely feedback or rubric-based scoring. In your role focusing on open-source engineering, you'll design clean, modular
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research and its efforts to put new knowledge and innovations directly into practice. The Laboratory of Metal Physics and Technology (LMPT), part of the Department of Materials at ETH Zurich, conducts
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to solve selected problems. Code and test the proposed solution (PoC), communicate results to stakeholders, and provide final reports of the work done and related outcomes. Present data science results
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content imaging for experimental workflows in biology and biochemistry. Project background The SCF's centralized instrument pool is accompanied by expert service provided by staff who offer instrument
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Switzerland's position in AI innovation. Job description As a machine learning research engineer, you will be responsible for developing and maintaining software for training large-scale neural networks, such as
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, data science, and industrial applications. As part of this position, you will: Develop and implement advanced Machine Learning models to analyze large datasets, including image and time-series data
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acquisitions) and exploring various imaging modes, including polarimetry, interferometry, and tomography. Numerous snow and glacier test sites are available worldwide for these topics, providing valuable ground
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. We have a co-working, ideation, and event space and offer coaching. In addition, we have a greatly equipped Makerspace that gives students access to the tools and equipment they need to prototype. We
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collected data Grade student answers and drawings by following a rubric Code session recordings with qualitative methods (using a predefined codebook) Collaborate with the researcher to refine the codebook as