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development. The successful candidate will contribute to the development of deep learning methods to predict reaction outcomes and optimal reaction conditions for organic reactions. The work will involve model
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chemical–biological pathway. The advertised positions will support these efforts through research on advanced carbon capture methods, process modelling and optimization, and biological CO2 valorization in
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challenge, making energy-efficient computing a critical research priority. This project addresses this challenge through a novel co-design approach that simultaneously optimizes both hardware and software
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large-scale, custom-designed digital signal processing readout system for the ATLAS experiment located at the CERN laboratory in Switzerland. Develop a prototype hardware implementation of different
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such as tissue culture, RNA extraction, qRTPCR, and others may be required. The position will optimize wind tunnel exposure methodology in consultation with the faculty supervisor, collect/manage data, and
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innovative employers in the region. With more than 6000 employees from 100 different countries, we are helping to build tomorrow's world every day. Through top scientific research, we push back boundaries and
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need optimally. Finally, in a multi-site study, we will test whether using this system and escalation pathways leads to better outcomes. We are seeking an enthusiastic, ambitious, clinical researcher
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who is at risk of deterioration. We will then investigate how to use this information to escalate the care of women in need optimally. Finally, in a multi-site study, we will test whether using
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to polymer building blocks. The work will involve developing suitable bacterial strains using synthetic biology tools for constructing optimal pathways, and protein engineering using rational design and
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through long-term impact assessment and optimization. The goal is to develop a framework to estimate carbon emissions across AI's development, operation, and use. This framework enables stakeholders