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. Weinstein (DTU Chemistry) to develop novel molecular ML methods and use them to control, steer, and learn from large scale wetlab experiments. You will deploy these methods in collaboration with Prof. Katrine
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. Responsibilities and qualifications Guided by initial AI predictions from the Weinstein group and microbiology results from the Tolker-Nielsen Lab, your main responsibilities will be to design, synthesize and
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stability prediction Collaborating closely with experimental researchers for iterative model refinement Publishing high-impact research at the intersection of AI and molecular design Supervising students
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materials, (d) Artificial Intelligence (AI) models to predict and control the construction process, (e) a digital twin / information backbone that enables cohesive operation of the design and production
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experimental verification of several RNA systems that can regulate gene expression, control enzyme proximity, sense product yields, and do molecular computations for feedback control. The successful candidate
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a team of 3 postdocs and 3 PhD students, who will work on design, characterization, and experimental verification of several RNA systems that can regulate gene expression, control enzyme proximity
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a team of 3 postdocs and 3 PhD students, who will work on design, characterization, and experimental verification of several RNA systems that can regulate gene expression, control enzyme proximity
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High-pressure XPS measurements may also be envisioned for most promising catalysts. Similarly, are we collaborating with CatTheory on predicting reaction pathways and microkinetic modelling screening