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Field
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geospatial workflows on an abstract level, using purpose-driven concepts and conceptual transformations; develop AI and machine learning based technology to automate the description and modeling of data
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analytics in a variety of biotechnological applications to faciliate real-time monitoring for in-depth biological understanding and subsequent automated process control. The Ottens lab works on implementation
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intuitive links between search parameters and the resulting geometry or performance outcomes. The result will be an LLM-driven framework giving designers clearer cause-effect control over generative shape
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control over generative shape optimisation. 2 – Explainable AI with LLMs for Transparent Decision-Making in Design Engineering This project combines classic XAI methods with LLM capabilities to generate
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PhD student for studying in vitro single-molecule transport across peroxisome mimics Job requirements The selective control of import and export across membrane-spanning pores is vital for our cells
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assays and RNA sequencing in iNeurons. Using advanced techniques such as automated live-cell imaging, electrophysiology and biomarker analyses, effective AONs will be selected. Ultimately, the goal is to
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control over generative shape optimisation. 2 – Explainable AI with LLMs for Transparent Decision-Making in Design Engineering This project combines classic XAI methods with LLM capabilities to generate
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vitro single-molecule transport across peroxisome mimics Job requirements The selective control of import and export across membrane-spanning pores is vital for our cells. Typically, the specificity
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at various levels. EAAS is hiring a total of 20 PhD/postdoc scientists to join the team, and our project/group leaders share the ambition of gender parity in hires across EAAS. Within this context we invite
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measurements of key organics, plus culture experiments, to uncover the biochemical pathways and environmental controls on methane formation and oxidation. Your job This work will enhance our understanding