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of high-throughput systems is maximized using design of experiment (DoE) approaches in order to efficiently explore the high-dimensional parameter space of the electrolysis processes. DoE is required
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relevant Master's degree (or exceptional Bachelor's) in biomedical/mechanical engineering, materials science, or computer science, with experience in mechanical design/textiles and programming (Python/MATLAB
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to the design of novel peptides and peptide aggregates able to induce spontaneous fusion. The peptides have been selected based on their biocompatibility and our exceptional experience with membrane-active
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field. You have knowledge of the functionality of CMOS digital circuits and technologies for implementing CMOS. You'll also have initial experience in the digital field with regard to circuit design of
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. Knowledge or experience in at least two of the following topics: a) Device physics (including simulation tools such as Sentaurus or mumax etc.). b) Basic circuit design (including tools such as SPICE
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engages with social history and lived experience and who is keen to develop their archival research skills, knowledge of riverine material culture and to employ object-centred design historical
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in Python programming. Experience with machine learning methods, bioinformatics, and data science. Familiarity with generative AI tools for protein design and protein language models. Knowledge
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understanding, capabilities and innovation, while inspiring and providing broad training to the next generations of researchers. Our values are Commitment, Collaboration and Transformation. Our research lines
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, XRD, IR spectroscopy, and BET analysis. Demonstrated ability to design and develop photo-activated sensor prototypes, with hands-on experience in hardware design. Familiarity with sourcing, assembling
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to design and develop photo-activated sensor prototypes, with hands-on experience in hardware design. Familiarity with sourcing, assembling, and troubleshooting sensor components or similar devices