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Field
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generation to automated experimentation. Yet applications of AI to real problems remain rare. We are looking for mathematicians with strong AI skills to move this frontier forward. In this postdoc you will
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intelligence-based automated interpretation of medical images, and new knowledge on the human visual system into the screening mammography reading process. Combining these new capabilities and new knowledge has
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of our Materials Vision Tech initiative, we focus on multi-element gradient thin film systems, i.e. their rapid deposition and automated multi-technique characterization. Within the Swiss-Polish innovation
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conditions. Write, document, and implement software code and scripts for data acquisition, device control, automation of testbeds, and simulations. Develop standard operating procedures (SOPs) for the MARVEL
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, the Postdoctoral Scholar will gain experience with state-of-the-art bioprocess technologies and expertise at the ABPDU, including continuous fermentation platforms and the Sartorius Ambr250 automated bioreactor
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on software-related developments, including: - Development and automation of test and monitoring software - Data acquisition and analysis including interfacing with databases - Monitoring of the quality
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explore new topics while playing nice in a team. Your main task will be the development, conceptualization, and eventual implementation of new design automation methods and software for your field, e.g
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automation, high-throughput data acquisition, and real-time data processing, offering a unique opportunity to advance S/TEM capabilities, publish impactful research, and collaborate with a diverse group of
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with biologists. You will report to the engineering lead on the project About the role The project will aim to develop fluid walls and associated automation workflows to enable microscale cell-based
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deposition and automated multi-technique characterization. Within the Swiss-Polish innovation project “DepoIon”, we develop physical vapor deposition (PVD) process control for solid state battery relevant