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Field
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, and chromatin-based methods. Cellular metabolic phenotyping, including high-resolution respirometry, will be used to connect molecular mechanisms to changes in cellular metabolism. The successful
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the integration of AI components transforms the nature of software systems (SE4AI). From an architectural perspective, the research investigates how the inclusion of AI elements—such as LLMs challenges conventional
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the enzyme RNA polymerase, with a small RNA molecule (6S RNA) acting as a hidden referee. 6S RNA determines which sigma factor gains access to the enzyme, which dictates whether the cell keeps growing
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must be inferred from the data. The overall goal is to develop reliable and robust statistical methods that can contribute to scientific understanding and inform decision-making and public policy
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, developing code, and creating novel tools and methods for advanced data analysis; supporting ongoing research activities, contributing to manuscript and grant writing, and preparing presentations
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sources of variation arise and propagate throughout the manufacturing process chain, from equipment performance and component processing to cell assembly, and how they can be characterized, quantified, and
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methods for assessments of key cost-driving phenomena. Who we are looking for The following requirements are mandatory: A doctoral degree in Mechanical engineering or similar, or an equivalent foreign
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Machine Learning group at TDB and SciLifeLab (Associate Professor Prashant Singh), which develops methods and software for simulation-based inference, generative models and robust machine learning, together
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of the system is still insufficiently understood. This project investigates the underlying fluid-structure interaction mechanisms and develops advanced numerical methods for high-fidelity simulation
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methods are developed in parallel, the postdoc will develop systems and services that make biological data accessible to AI and computational tools, collaborating closely with the Human Protein Atlas (HPA